正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

render skin

Lisana|| commission open||

14,266 subscribers

453,889 次观看 • 1 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

12 条评论

GreenHero3485 的头像

GreenHero34851 个月前

You're making it seem very easy. 😭 its not

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

😭😭

Grim Grey (Rock Crimson) 的头像

Grim Grey (Rock Crimson)1 个月前

How alluringly stunningly beautifully amazing!!

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

Thank you

Grim Grey (Rock Crimson) 的头像

Grim Grey (Rock Crimson)1 个月前

Thank you too for this wonderful sight!

💔Witches with Glitches🥀 的头像

💔Witches with Glitches🥀1 个月前

OH MY GOD (sorry) watching this just unlocked a part of my brain with rendering that i never considered before thank you 😭😭 i gotta test if my epiphany is true now 😵‍💫

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

Really.!That's awesome

RiriGurin ✦ 的头像

RiriGurin ✦1 个月前

I’m obsessed with how soft the rendering looks

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

Really! Thank you!

Nana🩵(cmm open) 的头像

Nana🩵(cmm open)1 个月前

this tummy is so yummy (ㅅ˙³˙)♡ I love this soft looking render and ur lines are so alive... I'm in love (*´˘`*)♡

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

Hehe thank you♥️♥️

Lisana|| commission open|| 的头像

Lisana|| commission open||1 个月前

My brushes are available here

相关视频

Skin is easy to render. Here's how!

Skin is easy to render. Here's how!

Philtomato 🍅

47,453 次观看 • 5 个月前

Be careful who you render help to, some are animals in human skin. Learn from this. Watch to the end.

Be careful who you render help to, some are animals in human skin. Learn from this. Watch to the end.

Adeolu. A

985,176 次观看 • 6 个月前

Skin Texturing in Substance Painter ✨ Learn how I create realistic skin textures step by step! 🎥 Check out the full tutorial on my YouTube channel 👇 #metahuman #unrealengine #substancepainter #madewithsubstance #render #texturing #gamedesign #digitalart #materials

Skin Texturing in Substance Painter ✨ Learn how I create realistic skin textures step by step! 🎥 Check out the full tutorial on my YouTube channel 👇 #metahuman #unrealengine #substancepainter #madewithsubstance #render #texturing #gamedesign #digitalart #materials

Javad Rajabzade

40,673 次观看 • 10 个月前

Mint Summer Skin — "Saltwater Taffy" With Hat & No Hat variant + combat animation showcase The skin seems to have higher render resolution compared to her base model outfit! Which one do you prefer with Hat or NO Hat? #NTE #NTEcreator

Mint Summer Skin — "Saltwater Taffy" With Hat & No Hat variant + combat animation showcase The skin seems to have higher render resolution compared to her base model outfit! Which one do you prefer with Hat or NO Hat? #NTE #NTEcreator

NTE & Ananta Info

11,390 次观看 • 17 天前

fixed bc why not Fun Yet - TOYMAKER SKIN CONCEPT | GRIMWORKS UST Visualizer and art by me and toymaker render by АZSFML 🔞 riko16riko16 hello again #Grimworks #fnaf #robloxasym

fixed bc why not Fun Yet - TOYMAKER SKIN CONCEPT | GRIMWORKS UST Visualizer and art by me and toymaker render by АZSFML 🔞 riko16riko16 hello again #Grimworks #fnaf #robloxasym

Bugai🔞(COMMS OPEN 0/2)

14,623 次观看 • 10 天前

Skin concept of Jason for #Forsaken/#forsakenroblox as the batter from OFF I was too lazy to make the slash , beheaded and the final blow Render by @Axo0oo

Skin concept of Jason for #Forsaken/#forsakenroblox as the batter from OFF I was too lazy to make the slash , beheaded and the final blow Render by @Axo0oo

SuperBonk06

151,929 次观看 • 1 年前

TOON NOLI ASSETS: - Full Render - Rig Showcase - SFX Showcase the SFX for the skin werent final and I was planning on remaking them and making actually good cause here I was just fucking around (same with the render) everything you see here was made by me #forsakenroblox

TOON NOLI ASSETS: - Full Render - Rig Showcase - SFX Showcase the SFX for the skin werent final and I was planning on remaking them and making actually good cause here I was just fucking around (same with the render) everything you see here was made by me #forsakenroblox

belle 🏳️‍⚧️

18,553 次观看 • 3 个月前

HappyHorse 1.1 is now available in ComfyUI as a Partner Node. Native audio. Multi-character consistency. Cinematic framing. All in one render pass. What's new in 1.1: → Dynamic expressiveness: Smoother motion, no more stiff movement → Enhanced R2V: Up to 9 reference images per generation → Multi-character consistency: Each character holds their look, zero cross-contamination → Flexible char × scene: Characters stay consistent as backgrounds change → Better instruction following: Handles 2,500+ char prompts, 6–8 scenes in one pass → Natural skin: Fixes shiny skin and over-sharpening for close-up commercial work → Cinematic language: Shot-reverse-shot, tracking shots, cohesive transitions → Upgraded audio: Tighter dialogue + SFX sync with emotional performance layered in Click the link below for the blog & the workflow 👇

HappyHorse 1.1 is now available in ComfyUI as a Partner Node. Native audio. Multi-character consistency. Cinematic framing. All in one render pass. What's new in 1.1: → Dynamic expressiveness: Smoother motion, no more stiff movement → Enhanced R2V: Up to 9 reference images per generation → Multi-character consistency: Each character holds their look, zero cross-contamination → Flexible char × scene: Characters stay consistent as backgrounds change → Better instruction following: Handles 2,500+ char prompts, 6–8 scenes in one pass → Natural skin: Fixes shiny skin and over-sharpening for close-up commercial work → Cinematic language: Shot-reverse-shot, tracking shots, cohesive transitions → Upgraded audio: Tighter dialogue + SFX sync with emotional performance layered in Click the link below for the blog & the workflow 👇

ComfyUI

17,266 次观看 • 2 个月前

$Google Gemini Nano Banana pro 3.0 Prompt { "subject": { "type": "chibi-style 3D character", "gender": "female", "features": { "hair": "pastel pink bob cut with soft bangs, stylized 3D strands", "eyes": "large expressive dark eyes, looking upward and to the side", "expression": "dreamy, slightly surprised, open mouth", "skin": "fair with soft pink blush on cheeks", "accessories": ["small gold hoop earrings", "delicate gold necklace with heart pendant"] }, "outfit": { "top": "tight-fitting dark brown long-sleeved crop top", "bottom": "high-waisted peach-colored joggers or harem pants", "shoes": "brown and tan platform sneakers" } }, "art_style": { "type": "3D render / C4D / Octane Render", "aesthetic": "soft claymorphism, smooth textures, toy-like aesthetic", "lighting": "soft cinematic lighting, warm sunlight, gentle shadows", "camera": "full body shot, eye-level, shallow depth of field (bokeh)" }, "environment": { "background": "blurred Mediterranean-style street, soft orange and cream buildings, arched doorway", "color_palette": ["pastel pink", "peach", "warm brown", "cream"] } }$

Google Gemini Nano Banana pro 3.0 Prompt { "subject": { "type": "chibi-style 3D character", "gender": "female", "features": { "hair": "pastel pink bob cut with soft bangs, stylized 3D strands", "eyes": "large expressive dark eyes, looking upward and to the side", "expression": "dreamy, slightly surprised, open mouth", "skin": "fair with soft pink blush on cheeks", "accessories": ["small gold hoop earrings", "delicate gold necklace with heart pendant"] }, "outfit": { "top": "tight-fitting dark brown long-sleeved crop top", "bottom": "high-waisted peach-colored joggers or harem pants", "shoes": "brown and tan platform sneakers" } }, "art_style": { "type": "3D render / C4D / Octane Render", "aesthetic": "soft claymorphism, smooth textures, toy-like aesthetic", "lighting": "soft cinematic lighting, warm sunlight, gentle shadows", "camera": "full body shot, eye-level, shallow depth of field (bokeh)" }, "environment": { "background": "blurred Mediterranean-style street, soft orange and cream buildings, arched doorway", "color_palette": ["pastel pink", "peach", "warm brown", "cream"] } }

Sharon Riley

83,444 次观看 • 8 个月前

Most AI girls get clocked immediately. Wrong lighting. Plastic skin. Eyes that don't focus. His account has been up eight months. Nobody asked once. 301K followers. $30,000 last month. The difference is one step everyone skips. He starts with a real reference photo. Not a prompt. Pinterest. Real girl. Real lighting. Then he writes the prompt around it. Feeds both into the model. Output looks like a camera roll photo. Not a render. Not AI. Just a girl. Full breakdown in the article below. Save it. 👇

Most AI girls get clocked immediately. Wrong lighting. Plastic skin. Eyes that don't focus. His account has been up eight months. Nobody asked once. 301K followers. $30,000 last month. The difference is one step everyone skips. He starts with a real reference photo. Not a prompt. Pinterest. Real girl. Real lighting. Then he writes the prompt around it. Feeds both into the model. Output looks like a camera roll photo. Not a render. Not AI. Just a girl. Full breakdown in the article below. Save it. 👇

wluha

14,450 次观看 • 2 个月前

AI video is no longer a lottery machine. With Seedance Enterprise 2.5 on BytePlus, shot generation hit rates go from 15 randomized rerolls down to 1–2 usable takes, delivering a 70%+ drop in actual costs and a massive boost in production efficiency. What makes it truly production-ready is its unmistakable human realism. Skin texture, eye light, and natural micro-expressions stay physically grounded under motion. Powered by 30-second single-shot generation and up to 50 multimodal references, characters and camera sweeps hold absolute consistency without faces drifting or features melting. Combine that with targeted localized editing, and you’re no longer fighting AI artifacts, you’re dropping high-fidelity footage straight into the final render. Seedance 2.5 API is about to launch on BytePlus, and Lumina is rolling it out soon!

AI video is no longer a lottery machine. With Seedance Enterprise 2.5 on BytePlus, shot generation hit rates go from 15 randomized rerolls down to 1–2 usable takes, delivering a 70%+ drop in actual costs and a massive boost in production efficiency. What makes it truly production-ready is its unmistakable human realism. Skin texture, eye light, and natural micro-expressions stay physically grounded under motion. Powered by 30-second single-shot generation and up to 50 multimodal references, characters and camera sweeps hold absolute consistency without faces drifting or features melting. Combine that with targeted localized editing, and you’re no longer fighting AI artifacts, you’re dropping high-fidelity footage straight into the final render. Seedance 2.5 API is about to launch on BytePlus, and Lumina is rolling it out soon!

Sharon Riley

45,772 次观看 • 1 个月前

Lechona at Lechona Serranos 📍Barranquilla, Colombia 🇨🇴 Explore Colombia: Lechona is a spectacular masterpiece of traditional Colombian gastronomy requiring immense patience and an incredibly elaborate artisanal preparation process. While historically rooted in the Tolima region this massive roasted pork dish has become a highly celebrated festive staple across the entire country. The meticulous preparation begins by carefully prepping the meat and generously rubbing it with a unique blend of local spices. The interior is then systematically built by layering seasoned rice tender yellow peas smoked bacon and rich chunks of marinated lean pork. Once fully constructed the entire preparation is slowly roasted in an oven for over twelve hours. This extended exposure to steady heat is absolutely crucial as it guarantees a perfectly golden crispy skin while allowing the internal fats to slowly render and baste the dense savory filling.

Lechona at Lechona Serranos 📍Barranquilla, Colombia 🇨🇴 Explore Colombia: Lechona is a spectacular masterpiece of traditional Colombian gastronomy requiring immense patience and an incredibly elaborate artisanal preparation process. While historically rooted in the Tolima region this massive roasted pork dish has become a highly celebrated festive staple across the entire country. The meticulous preparation begins by carefully prepping the meat and generously rubbing it with a unique blend of local spices. The interior is then systematically built by layering seasoned rice tender yellow peas smoked bacon and rich chunks of marinated lean pork. Once fully constructed the entire preparation is slowly roasted in an oven for over twelve hours. This extended exposure to steady heat is absolutely crucial as it guarantees a perfectly golden crispy skin while allowing the internal fats to slowly render and baste the dense savory filling.

TasteAtlas

115,217 次观看 • 5 个月前

It’s the little moments we wish lasted longer Created with seedance 2.5 on TapNow A 30-second, 1080p, 16:9 ultra-photorealistic everyday-life video of a young Korean woman in Seoul. It should feel like a casual personal lifestyle video, not an advertisement or cinematic film. Character: Mid-20s Korean woman, natural features and skin texture, long dark-brown hair in a low ponytail, minimal makeup. Dusty-rose T-shirt, light-wash straight jeans, white canvas sneakers, olive-green shoulder bag, silver bracelet and earrings. Keep her face, hair, outfit and accessories perfectly consistent. 0–5s: She leaves a modest Seoul apartment, adjusts her bag and walks through a quiet neighborhood. Natural handheld camera, relaxed movement. 5–10s: She passes a bakery, convenience store and pedestrians, briefly glancing at a shop window. Natural street ambience. 10–15s: She notices a local mobile shop, enters, and points to an iPhone 18 Pro. A salesperson hands it to her. 15–20s: She examines the phone, turns on the screen, opens the camera and takes a quick photo. She smiles naturally. 20–25s: A sealed iPhone 18 Pro box is placed on the counter. She pays and puts it carefully into her shoulder bag. 25–30s: She leaves the shop, walks down the Seoul sidewalk and briefly smiles while looking at the new phone box in her bag. End naturally as she walks away. Style: Real handheld personal-video feel, subtle camera shake, natural autofocus and exposure changes, realistic motion blur, authentic Seoul environment, natural skin and hair, realistic hands and phone interaction. No dramatic camera moves, slow motion, drone shots or polished commercial look. Audio: Natural location sounds only—footsteps, traffic, pedestrians, shop ambience, door and phone handling sounds. No music, voice-over, captions, subtitles or watermark. Negative: CGI, 3D render, beauty filter, plastic skin, exaggerated expressions, posing, futuristic showroom, luxury commercial, fake or morphing phone, changing phone design, distorted hands, extra fingers, inconsistent face, hair or clothing, artificial lighting.

It’s the little moments we wish lasted longer Created with seedance 2.5 on TapNow A 30-second, 1080p, 16:9 ultra-photorealistic everyday-life video of a young Korean woman in Seoul. It should feel like a casual personal lifestyle video, not an advertisement or cinematic film. Character: Mid-20s Korean woman, natural features and skin texture, long dark-brown hair in a low ponytail, minimal makeup. Dusty-rose T-shirt, light-wash straight jeans, white canvas sneakers, olive-green shoulder bag, silver bracelet and earrings. Keep her face, hair, outfit and accessories perfectly consistent. 0–5s: She leaves a modest Seoul apartment, adjusts her bag and walks through a quiet neighborhood. Natural handheld camera, relaxed movement. 5–10s: She passes a bakery, convenience store and pedestrians, briefly glancing at a shop window. Natural street ambience. 10–15s: She notices a local mobile shop, enters, and points to an iPhone 18 Pro. A salesperson hands it to her. 15–20s: She examines the phone, turns on the screen, opens the camera and takes a quick photo. She smiles naturally. 20–25s: A sealed iPhone 18 Pro box is placed on the counter. She pays and puts it carefully into her shoulder bag. 25–30s: She leaves the shop, walks down the Seoul sidewalk and briefly smiles while looking at the new phone box in her bag. End naturally as she walks away. Style: Real handheld personal-video feel, subtle camera shake, natural autofocus and exposure changes, realistic motion blur, authentic Seoul environment, natural skin and hair, realistic hands and phone interaction. No dramatic camera moves, slow motion, drone shots or polished commercial look. Audio: Natural location sounds only—footsteps, traffic, pedestrians, shop ambience, door and phone handling sounds. No music, voice-over, captions, subtitles or watermark. Negative: CGI, 3D render, beauty filter, plastic skin, exaggerated expressions, posing, futuristic showroom, luxury commercial, fake or morphing phone, changing phone design, distorted hands, extra fingers, inconsistent face, hair or clothing, artificial lighting.

Anissa

16,147 次观看 • 4 天前

A Bonus render of Electron Holography for our Quantum Mechanics Lecture Series. We’re staging a TEM-style electron holography shot as a single 3D scene. A coherent electron wave ψ(x,y,t) enters from the left as a localized packet, gets split by a thin biprism phase wedge, then bends around a central nanoring that stands in for an enclosed magnetic flux. The wave evolves by Schrödinger dynamics, so its intensity ρ=|ψ|² is literally the electron detection probability density, while the probability current j=(1/m)Im(ψ*∇ψ) acts like a conserved flow of that density across the plane. The main surface is a living whose height tracks |ψ| and whose skin color cycles with arg(ψ). On top of it, luminous current ribbons trace streamlines of v=j/(ρ+ε), so you can see how phase gradients steer the flow around the ring and back into interference. High above, a tilted detector/hologram screen shows the off-axis fringe image you’d measure (intensity after mixing with a reference wave), while a porcelain bead marks the centroid ⟨x⟩(t) and flux threads through the ring pulse in sync with the Aharonov-Bohm phase knob φ_AB(t). See our lecture series for details. #QuantumMechanics #ElectronHolography #MathematicalPhysics #Physics

A Bonus render of Electron Holography for our Quantum Mechanics Lecture Series. We’re staging a TEM-style electron holography shot as a single 3D scene. A coherent electron wave ψ(x,y,t) enters from the left as a localized packet, gets split by a thin biprism phase wedge, then bends around a central nanoring that stands in for an enclosed magnetic flux. The wave evolves by Schrödinger dynamics, so its intensity ρ=|ψ|² is literally the electron detection probability density, while the probability current j=(1/m)Im(ψ*∇ψ) acts like a conserved flow of that density across the plane. The main surface is a living whose height tracks |ψ| and whose skin color cycles with arg(ψ). On top of it, luminous current ribbons trace streamlines of v=j/(ρ+ε), so you can see how phase gradients steer the flow around the ring and back into interference. High above, a tilted detector/hologram screen shows the off-axis fringe image you’d measure (intensity after mixing with a reference wave), while a porcelain bead marks the centroid ⟨x⟩(t) and flux threads through the ring pulse in sync with the Aharonov-Bohm phase knob φ_AB(t). See our lecture series for details. #QuantumMechanics #ElectronHolography #MathematicalPhysics #Physics

Mathelirium

14,252 次观看 • 8 个月前

This guy got Claude to take control of Arcads and generate hyperrealistic UGC ads with a consistent AI actor, from a 7-word prompt, and now e-com brands pay him $1,500 per video to clone the setup. He got tired of watching DTC brands burn $4K on a photoshoot that dies the second a product angle changes, so he built a 2-prompt workflow that turns one product photo into scroll-stopping UGC without a single model, camera, or casting call. Here's the exact breakdown: → Claude is the director, Arcads is the studio. You never write a real prompt, you write one sentence → Type 7 words: "create a character sheet of a UGC actress on Arcads." Claude expands it into a 40-line spec: warm skin tone, high ponytail, gold hoops, white AirPods, athletic build, then takes control of Arcads itself → Arcads renders a 6-angle character sheet: front, back, profile, 3/4, two portraits, one consistent face locked across all of them → You download the grid and drop it back into Claude with one product photo → Second prompt, 8 words: "use Seedance 2.0 on Arcads to create natural UGC" → Claude writes the full shot list: timecodes, "1:03 AM clock zoom," the trackpad scroll, the arm pull that drags the product into frame, "delivery: casual, energetic," "ends on a wink + air kiss" → Arcads cuts the yellow Vans print onto an actor who was wearing all black in the grid. Real fabric folds, real light, zero warping → Final render: lip-sync locked to consonants, head not glued to the camera, a girl filming at 1am on her bed The key move 96% of people skip: you can't put the product on the actor before you lock the character sheet. If you drop a product photo onto a face that isn't locked across angles, the identity drifts frame to frame. The jaw resets. The skin tone shifts. The print slides off the fabric. The whole thing screams "AI" and your CTR dies in the first 2 seconds. His system locks the 6-view sheet first, so Arcads has one real human to dress, and the top lands with natural folds even though the grid never had it. One apparel brand ran 20 variants off a single product photo and found a winner in 36 hours, because the clips read like organic UGC, not a studio ad. Brands now pay him $1,500 per avatar build + $340/month to keep dropping fresh video batches on every new product. The entire thing runs on two prompts and one laptop. No photographer. No model agency. No product samples on set. Just two sentences, one product photo, and the discipline to lock the character before you render a single second of movement.

Shade

15,227 次观看 • 3 个月前

👇BEHOLD: The proof people asked for; 30 seconds of Seedance 2.5 480p → Topaz 4K using upscaling. Topaz 4K on top, 480p source below. Same frame. Watch the closeups from :04 onwards for the best comparison of the subject for where the most detail in the upscale is visible. (Best compared on full screen) 💻 The Process: This clip was upscaled using Topaz's "Rhea" model, which does 4x upscaling. With the resolution of our original 21:9 aspect ratio clip increased to: 3440x1498 The "Proteus" model is better for general upscaling of 720p; "Rhea" makes 480p footage look as good as 4K clips upscaled from 720p or 1080p. 💭Thoughts: The only downside for using Rhea is the render time if you aren't running on decent hardware and a noticable, slight grain on renders. Otherwise, I wholly recommend Rhea over Proteus if you want razor sharpness in 480p clips. For general upscaling and speed, stick with Proteus which also dials back the sharpness for the nice soft filmic look. Skin holds texture instead of going plastic, the cloth weave comes back, and the background details fill in. 🗒️Note: [Differences may seem subtle here due to X's video compression. I know a lot of these comparisons soften the low-res side on purpose to make the jump look bigger. Keeping it sincere here. Cost breakdown coming soon.]

👇BEHOLD: The proof people asked for; 30 seconds of Seedance 2.5 480p → Topaz 4K using upscaling. Topaz 4K on top, 480p source below. Same frame. Watch the closeups from :04 onwards for the best comparison of the subject for where the most detail in the upscale is visible. (Best compared on full screen) 💻 The Process: This clip was upscaled using Topaz's "Rhea" model, which does 4x upscaling. With the resolution of our original 21:9 aspect ratio clip increased to: 3440x1498 The "Proteus" model is better for general upscaling of 720p; "Rhea" makes 480p footage look as good as 4K clips upscaled from 720p or 1080p. 💭Thoughts: The only downside for using Rhea is the render time if you aren't running on decent hardware and a noticable, slight grain on renders. Otherwise, I wholly recommend Rhea over Proteus if you want razor sharpness in 480p clips. For general upscaling and speed, stick with Proteus which also dials back the sharpness for the nice soft filmic look. Skin holds texture instead of going plastic, the cloth weave comes back, and the background details fill in. 🗒️Note: [Differences may seem subtle here due to X's video compression. I know a lot of these comparisons soften the low-res side on purpose to make the jump look bigger. Keeping it sincere here. Cost breakdown coming soon.]

God's Way Foundation

23,702 次观看 • 17 天前

Every time a new AI model demonstrates an ability to manipulate or generate media, it's celebrated as if we're witnessing these capabilities for the first time. This framing misses a crucial point: most of these capabilities have existed for decades. We just used different technology to accomplish them. What's changing now is that AI is allowing media generation and editing to be more accessible to many more - both in terms of cost and ease of use. Take David Fincher's The Social Network from 2010. The Winklevoss twins were played by two different actors, but Armie Hammer's face was digitally placed onto Josh Pence's body. What we call deepfakes today was just traditional VFX pipelines then. The process involved high-resolution facial scanning, detailed 3D modeling, precise facial rigging, and frame-by-frame tracking. The VFX team created photorealistic digital doubles, mapped accurate skin textures, and manually refined each transformation until the result was imperceptible. Most viewers never noticed - which is exactly the point. The best CGI is invisible CGI. This wasn't unique. Hollywood has been digitally transforming actors for decades through well-established technical pipelines: photogrammetry, facial capture, advanced compositing, and physics-based rendering. The question isn't whether we can do it - that has already been answered. Previously, two factors kept this technology contained: technical complexity and cost. Traditional graphics pipelines required specialized infrastructure - from high-end capture equipment to render farms - and deep technical expertise across multiple disciplines. "Fix it in post" meant teams of technical artists working with proprietary tools and complex workflows. More importantly, it was expensive - often millions per shot. Digital effects at this level are reserved for big-budget productions. AI isn't changing what's possible - it's changing the implementation stack. The same transformations that once required extensive hardware, specialized software, and teams of technical artists are being consolidated by generative and world models. The technology is moving from complex production pipelines to end-to-end solutions that anyone can use. Like Act-One (who said Act-Two?). What becomes possible when these capabilities are democratized? When sophisticated effects and graphics become accessible to many more filmmakers? When actors will be able to do more, in more languages, for more audiences? What happens when the technical and financial barriers to high-end content creation disappear?

Every time a new AI model demonstrates an ability to manipulate or generate media, it's celebrated as if we're witnessing these capabilities for the first time. This framing misses a crucial point: most of these capabilities have existed for decades. We just used different technology to accomplish them. What's changing now is that AI is allowing media generation and editing to be more accessible to many more - both in terms of cost and ease of use. Take David Fincher's The Social Network from 2010. The Winklevoss twins were played by two different actors, but Armie Hammer's face was digitally placed onto Josh Pence's body. What we call deepfakes today was just traditional VFX pipelines then. The process involved high-resolution facial scanning, detailed 3D modeling, precise facial rigging, and frame-by-frame tracking. The VFX team created photorealistic digital doubles, mapped accurate skin textures, and manually refined each transformation until the result was imperceptible. Most viewers never noticed - which is exactly the point. The best CGI is invisible CGI. This wasn't unique. Hollywood has been digitally transforming actors for decades through well-established technical pipelines: photogrammetry, facial capture, advanced compositing, and physics-based rendering. The question isn't whether we can do it - that has already been answered. Previously, two factors kept this technology contained: technical complexity and cost. Traditional graphics pipelines required specialized infrastructure - from high-end capture equipment to render farms - and deep technical expertise across multiple disciplines. "Fix it in post" meant teams of technical artists working with proprietary tools and complex workflows. More importantly, it was expensive - often millions per shot. Digital effects at this level are reserved for big-budget productions. AI isn't changing what's possible - it's changing the implementation stack. The same transformations that once required extensive hardware, specialized software, and teams of technical artists are being consolidated by generative and world models. The technology is moving from complex production pipelines to end-to-end solutions that anyone can use. Like Act-One (who said Act-Two?). What becomes possible when these capabilities are democratized? When sophisticated effects and graphics become accessible to many more filmmakers? When actors will be able to do more, in more languages, for more audiences? What happens when the technical and financial barriers to high-end content creation disappear?

Cristóbal Valenzuela

30,627 次观看 • 1 年前

Quantum mechanics has a reputation for being mystical mainly because people skip the rules and jump to interpretations. In this lecture series, we’re doing the opposite. We start from the rules, follow the algebra, and let the picture be the calculation. Classical Probability Theory combines alternatives by adding their probabilities. Quantum Theory combines them one step earlier…add complex amplitudes first, then square at the end. That swap in order is everything. Expand |a₁ + a₂|² and you don’t just get |a₁|² + |a₂|²…you get a cross-term, 2 Re(a₁ a₂*). Its sign is set by phase, so the same two contributions can reinforce or cancel. Interference is just the algebra of squaring a sum. In the 3D render, the surface height is proportional to |a(x)| (so peaks become bright bands after squaring), while the surface skin is colored by the local phase arg(a(x)). As the phase knob φ(t) is swept on path 2, the cross-term oscillates, and you literally watch the interference ridges slide across the screen. We model a detector screen with coordinates x in R² (think x = (x,y)). A quantum state assigns a complex amplitude a(x). The rule for outcomes is p(x) = |a(x)|² Now the key situation: two coherent alternatives contribute to the same outcome x. Let their amplitudes be a₁(x) and a₂(x). Quantum says a(x) = a₁(x) + a₂(x) So the probability density becomes p(x) = |a₁(x) + a₂(x)|² Expand it (this is the whole episode): p(x) = (a₁ + a₂)(a₁* + a₂*) = |a₁|² + |a₂|² + a₁ a₂* + a₁* a₂ = |a₁|² + |a₂|² + 2 Re(a₁ a₂*) That last term is the interference term. It can be positive or negative. To see phase explicitly, write each contribution in polar form: a₁(x) = r₁(x) exp(i θ₁(x)) a₂(x) = r₂(x) exp(i θ₂(x)) Then a₁ a₂* = r₁ r₂ exp(i(θ₁ − θ₂)) So the cross-term is 2 Re(a₁ a₂*) = 2 r₁ r₂ cos(θ₁(x) − θ₂(x)) That’s the fringe engine: p(x) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x)) Now the phase knob we animate: Add a controllable phase shift φ to path 2: a₂(x) → a₂(x) exp(i φ) Then Δθ(x) → Δθ(x) − φ, so p(x; φ) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x) − φ) As φ changes smoothly, the bright/dark pattern slides continuously. Same setup, same geometry, same magnitudes r₁,r₂, only phase changed. #QuantumMechanics #WaveInterference #ComplexAmplitudes #DoubleSlit #Physics #Mathematics

Quantum mechanics has a reputation for being mystical mainly because people skip the rules and jump to interpretations. In this lecture series, we’re doing the opposite. We start from the rules, follow the algebra, and let the picture be the calculation. Classical Probability Theory combines alternatives by adding their probabilities. Quantum Theory combines them one step earlier…add complex amplitudes first, then square at the end. That swap in order is everything. Expand |a₁ + a₂|² and you don’t just get |a₁|² + |a₂|²…you get a cross-term, 2 Re(a₁ a₂). Its sign is set by phase, so the same two contributions can reinforce or cancel. Interference is just the algebra of squaring a sum. In the 3D render, the surface height is proportional to |a(x)| (so peaks become bright bands after squaring), while the surface skin is colored by the local phase arg(a(x)). As the phase knob φ(t) is swept on path 2, the cross-term oscillates, and you literally watch the interference ridges slide across the screen. We model a detector screen with coordinates x in R² (think x = (x,y)). A quantum state assigns a complex amplitude a(x). The rule for outcomes is p(x) = |a(x)|² Now the key situation: two coherent alternatives contribute to the same outcome x. Let their amplitudes be a₁(x) and a₂(x). Quantum says a(x) = a₁(x) + a₂(x) So the probability density becomes p(x) = |a₁(x) + a₂(x)|² Expand it (this is the whole episode): p(x) = (a₁ + a₂)(a₁ + a₂) = |a₁|² + |a₂|² + a₁ a₂ + a₁* a₂ = |a₁|² + |a₂|² + 2 Re(a₁ a₂) That last term is the interference term. It can be positive or negative. To see phase explicitly, write each contribution in polar form: a₁(x) = r₁(x) exp(i θ₁(x)) a₂(x) = r₂(x) exp(i θ₂(x)) Then a₁ a₂ = r₁ r₂ exp(i(θ₁ − θ₂)) So the cross-term is 2 Re(a₁ a₂*) = 2 r₁ r₂ cos(θ₁(x) − θ₂(x)) That’s the fringe engine: p(x) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x)) Now the phase knob we animate: Add a controllable phase shift φ to path 2: a₂(x) → a₂(x) exp(i φ) Then Δθ(x) → Δθ(x) − φ, so p(x; φ) = r₁² + r₂² + 2 r₁ r₂ cos(Δθ(x) − φ) As φ changes smoothly, the bright/dark pattern slides continuously. Same setup, same geometry, same magnitudes r₁,r₂, only phase changed. #QuantumMechanics #WaveInterference #ComplexAmplitudes #DoubleSlit #Physics #Mathematics

Mathelirium

81,661 次观看 • 8 个月前