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MiniMax M3 might be the most underrated coding model right now. I gave it nothing but a screenshot of a chaotic 90s GeoCities-style fan page, no HTML source, just the image + the asset files, and told it to rebuild the whole thing as a sleek Apple-style 2026 site.... show more

stevibe

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21,206 Aufrufe • vor 2 Monaten •via X (Twitter)

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MiniMax M3 just dropped — their first natively multimodal model. So I ran it through my form-filling test. (The model has to place each element at the right pixel position on a blank form image, not type into a field.) Verdict: it got everything on the paper. > Name, DOB, ID, gender, marital status, nationality, email, phone, address, postal code, all there. > Best character spacing I've seen yet: it actually calculates the gap between each character, clean across the DOB and number boxes > A few fields slightly misaligned, but every piece of data made it onto the form The reasoning chain is the interesting part: it does the easy fields first, then works into the tight one-char-per-box fields, reasoning through y-coordinates, baselines, and label clearance in obsessive detail. The cost: 40:33 and 126.7k output tokens. That's a long think — but it's MiniMax's first multimodal model, and it nailed the content.

MiniMax M3 just dropped — their first natively multimodal model. So I ran it through my form-filling test. (The model has to place each element at the right pixel position on a blank form image, not type into a field.) Verdict: it got everything on the paper. > Name, DOB, ID, gender, marital status, nationality, email, phone, address, postal code, all there. > Best character spacing I've seen yet: it actually calculates the gap between each character, clean across the DOB and number boxes > A few fields slightly misaligned, but every piece of data made it onto the form The reasoning chain is the interesting part: it does the easy fields first, then works into the tight one-char-per-box fields, reasoning through y-coordinates, baselines, and label clearance in obsessive detail. The cost: 40:33 and 126.7k output tokens. That's a long think — but it's MiniMax's first multimodal model, and it nailed the content.

stevibe

27,383 Aufrufe • vor 2 Monaten

made a nothing design skill for claude code. tell it "nothing style" and it builds the whole thing. tokens, components, dark+light. go grab it, it’s open source:

made a nothing design skill for claude code. tell it "nothing style" and it builds the whole thing. tokens, components, dark+light. go grab it, it’s open source:

Dom

288,164 Aufrufe • vor 4 Monaten

Mistral OCR 4 turned a handwritten calculus exam into clean LaTeX! We gave it a photo of a hand-written exam page. The model read the handwriting and rebuilt every formula into structured digital text Output: Time: 5.1s · Cost: $0.09 Formulas came through exactly right - the hard part was nailed. The graph, unfortunately, it didn’t redraw. But that’s the telling part: most OCR tools just dump the text and quietly drop the figure. OCR 4 caught the plot, boxed it, and tagged it as a chart. It doesn’t get redrawn, but it gets read and accounted for

Mistral OCR 4 turned a handwritten calculus exam into clean LaTeX! We gave it a photo of a hand-written exam page. The model read the handwriting and rebuilt every formula into structured digital text Output: Time: 5.1s · Cost: $0.09 Formulas came through exactly right - the hard part was nailed. The graph, unfortunately, it didn’t redraw. But that’s the telling part: most OCR tools just dump the text and quietly drop the figure. OCR 4 caught the plot, boxed it, and tagged it as a chart. It doesn’t get redrawn, but it gets read and accounted for

atomic.chat

419,536 Aufrufe • vor 1 Monat

SOMEONE JUST VIBECODED A PROGRAM THAT DOWNLOADS ANY WEBSITE ON THE INTERNET every $35,000 agency site is now yours to rip clean for $0 fully open source, save it before it's gone you paste one url and it does the rest: → crawls the entire site → grabs every file: html, css, js, images, even the fonts → rewrites every link to run fully offline → packs it all into a downloadable zip runs entirely in the browser, nothing to install or sign up for point it at any site you admire and the whole front-end is yours: → clone it → archive it before it dies → crack open exactly how it was built the thing agencies gatekeep for five figures is now a 10-second download bookmark this one

SOMEONE JUST VIBECODED A PROGRAM THAT DOWNLOADS ANY WEBSITE ON THE INTERNET every $35,000 agency site is now yours to rip clean for $0 fully open source, save it before it's gone you paste one url and it does the rest: → crawls the entire site → grabs every file: html, css, js, images, even the fonts → rewrites every link to run fully offline → packs it all into a downloadable zip runs entirely in the browser, nothing to install or sign up for point it at any site you admire and the whole front-end is yours: → clone it → archive it before it dies → crack open exactly how it was built the thing agencies gatekeep for five figures is now a 10-second download bookmark this one

Argona

125,940 Aufrufe • vor 1 Monat

Qwen3.6 35B A3B can't fill out a paper form on its own. But give it NVIDIA's LocateAnything-3B — the #1 trending model on HuggingFace — as its eyes, and the two small models get it done together. (The test: place each element at the right pixel position on a blank form image, not type into a field.) Setup: > Qwen is the brain (main model), LocateAnything is the eyes (helper model acting as a tool). > I gave Qwen a new tool: ask "where's the email field?" and LocateAnything returns the exact x, y, width, height. > The blue boxes on the screen are its detections. Look how tight they are — it nails every field. Result: > Qwen3.6 35B A3B + LocateAnything-3B: form completed, all info correct. > Name, DOB, ID, gender, marital status, nationality, email, phone, address, postal code: all landed in the right field areas. > Character-box alignment still a touch loose, but every value is where it belongs. > 9m10s, 224.5k input, 24.3k output, 21 turns. Why it matters: > Qwen alone can't finish this test. Bolt on a 3B model that does exactly one thing > locate > and suddenly it can. > A combination of small models can do the work of a single large one.

Qwen3.6 35B A3B can't fill out a paper form on its own. But give it NVIDIA's LocateAnything-3B — the #1 trending model on HuggingFace — as its eyes, and the two small models get it done together. (The test: place each element at the right pixel position on a blank form image, not type into a field.) Setup: > Qwen is the brain (main model), LocateAnything is the eyes (helper model acting as a tool). > I gave Qwen a new tool: ask "where's the email field?" and LocateAnything returns the exact x, y, width, height. > The blue boxes on the screen are its detections. Look how tight they are — it nails every field. Result: > Qwen3.6 35B A3B + LocateAnything-3B: form completed, all info correct. > Name, DOB, ID, gender, marital status, nationality, email, phone, address, postal code: all landed in the right field areas. > Character-box alignment still a touch loose, but every value is where it belongs. > 9m10s, 224.5k input, 24.3k output, 21 turns. Why it matters: > Qwen alone can't finish this test. Bolt on a 3B model that does exactly one thing > locate > and suddenly it can. > A combination of small models can do the work of a single large one.

stevibe

150,016 Aufrufe • vor 2 Monaten

Step 1 : input your char reference, poster and your product into GPT Image 2 and then put the prompt : Use the woman on image 1 as the main subject. create a vertical poster ad inspired by the reference poster style. show the image 1 woman holding the kimchi jar with her left hand, while the right hand eating kimchi to her mouth. with framing wide lens, low angle from the reference poster. This step is where you lock the visual direction. Step 2 : take the generated image into Seedance 2.0 and convert it into motion. Set it to 1080p if your design includes a lot of typography, this helps preserve text clarity. You can also strengthen your prompt by adding keywords like: “dynamic motion design commercial advertisement” to push the result closer to a polished ad style. Important note : If your design contains heavy typography, expect some inconsistencies in text rendering. The best approach is to generate multiple variations and select the cleanest result. For this sample, I generated it 4 times before landing on the final version.

Step 1 : input your char reference, poster and your product into GPT Image 2 and then put the prompt : Use the woman on image 1 as the main subject. create a vertical poster ad inspired by the reference poster style. show the image 1 woman holding the kimchi jar with her left hand, while the right hand eating kimchi to her mouth. with framing wide lens, low angle from the reference poster. This step is where you lock the visual direction. Step 2 : take the generated image into Seedance 2.0 and convert it into motion. Set it to 1080p if your design includes a lot of typography, this helps preserve text clarity. You can also strengthen your prompt by adding keywords like: “dynamic motion design commercial advertisement” to push the result closer to a polished ad style. Important note : If your design contains heavy typography, expect some inconsistencies in text rendering. The best approach is to generate multiple variations and select the cleanest result. For this sample, I generated it 4 times before landing on the final version.

DStudioproject

11,413 Aufrufe • vor 3 Monaten

Fable is amazing!! I gave it a prompt to "build a minecraft style roller coaster for the stock market" And it just did it. ONE SHOT! 😲🎢:

Fable is amazing!! I gave it a prompt to "build a minecraft style roller coaster for the stock market" And it just did it. ONE SHOT! 😲🎢:

jinjingliang

175,542 Aufrufe • vor 2 Monaten

Tested Hailuo AI (MiniMax)’s MiniMax H3 through early access by turning a single wireless-earbuds image into a complete product commercial. From the charging case opening and the earbuds lifting into frame to the close-up rotations and final hero shot, MiniMax H3 handled the sequence with smooth motion and strong product consistency. What stood out to me was how well it maintained the product’s design while adding controlled, commercial-style movement. This makes it especially useful for creating polished brand visuals from simple reference inputs. Explore Hailuo AI: #hailuoai #MiniMaxH3 #hailuo #H3

Marry claire

17,155 Aufrufe • vor 10 Tagen

The future of AI in web development? This app generates code and images to convert a screenshot into HTML/Tailwind CSS. I just gave it a screenshot of my X feed, and look what it produced (Notes & link in the comments):

The future of AI in web development? This app generates code and images to convert a screenshot into HTML/Tailwind CSS. I just gave it a screenshot of my X feed, and look what it produced (Notes & link in the comments):

Alvaro Cintas

303,527 Aufrufe • vor 2 Jahren

Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)

Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)

Mike Futia

57,779 Aufrufe • vor 2 Monaten

MiniMax H3 × Midjourney V8.2 I just made a Hollywood-style space movie scene on Pollo AI and the result is insane. Midjourney V8.2 created the cinematic reference image. Then MiniMax H3 turned it into a full sci-fi sequence with an alien mothership, zero-gravity destruction, space battles, cinematic dialogue and synchronized audio. All from one detailed prompt.

MiniMax H3 × Midjourney V8.2 I just made a Hollywood-style space movie scene on Pollo AI and the result is insane. Midjourney V8.2 created the cinematic reference image. Then MiniMax H3 turned it into a full sci-fi sequence with an alien mothership, zero-gravity destruction, space battles, cinematic dialogue and synchronized audio. All from one detailed prompt.

Katherine

51,580 Aufrufe • vor 5 Tagen

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.

Sudo su

37,201 Aufrufe • vor 5 Monaten

seedance 2 is crazy... this model works completely different than anything else out there i gave it a very vague prompt with a starting image and it handled all the b-rolls, voiceover, transitions - without me specifying any of that the way this works, it looks like AI ugc automation might actually be possible now if you build the right system around it still a lot to play around with but this is looking very promising

seedance 2 is crazy... this model works completely different than anything else out there i gave it a very vague prompt with a starting image and it handled all the b-rolls, voiceover, transitions - without me specifying any of that the way this works, it looks like AI ugc automation might actually be possible now if you build the right system around it still a lot to play around with but this is looking very promising

Miko

22,466 Aufrufe • vor 6 Monaten

What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark

What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark

Ai Arainz

104,348 Aufrufe • vor 2 Monaten

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

Gipp 🦅

295,658 Aufrufe • vor 2 Monaten

Nothing I want more than Dillon to get back on track and just tear it up the rest of the season but it is a struggle right now.

Nothing I want more than Dillon to get back on track and just tear it up the rest of the season but it is a struggle right now.

Andy Herman

369,090 Aufrufe • vor 2 Jahren

Every soul is a unique perspective of the same eternal Consciousness. To harm another is to wound another finger of the same hand. To know yourself is to know the Whole. Suffering is a lesson that must be learned, for it is through it that we awaken and become one with the Divine. I hope the animation won't give you nightmares.

Every soul is a unique perspective of the same eternal Consciousness. To harm another is to wound another finger of the same hand. To know yourself is to know the Whole. Suffering is a lesson that must be learned, for it is through it that we awaken and become one with the Divine. I hope the animation won't give you nightmares.

Open Minded Approach

11,207 Aufrufe • vor 9 Tagen

MiniMax is the James Bond of AI agents. It uses the world's first open-weight model (MiniMax-M1), and it squeezes every bit of power from it. The agent takes a prompt and does more than any other agent in the market right now: 1. It can do Deep Research 2. It can write code 3. It can design web pages 4. It can build 3D models I built 5 different experiences using MiniMax and recorded them for you:

MiniMax is the James Bond of AI agents. It uses the world's first open-weight model (MiniMax-M1), and it squeezes every bit of power from it. The agent takes a prompt and does more than any other agent in the market right now: 1. It can do Deep Research 2. It can write code 3. It can design web pages 4. It can build 3D models I built 5 different experiences using MiniMax and recorded them for you:

Santiago

44,730 Aufrufe • vor 1 Jahr

THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.

THE DEPTH MAP TRICK THAT FIXED DANCE ACCURACY IN SEEDANCE 2.0 Feed the model a video of someone dancing and it tries to interpret everything- the person, the clothes, the lighting, the room, and somewhere in there, the movement. Feed it a depth map and there's nothing left to interpret but the motion. Most creators trying to transfer a dance to a character reference the source footage directly, then wonder why the choreography drifts. The problem isn't the model - it's that you handed it ten variables when you only wanted one. Here's the workflow 1. Lock the character reference in GPT Image 2 first -face, build, costume, so identity holds independently of whatever motion gets applied to it 2. Convert the source dance footage into a depth map instead of using the raw video -this strips out the original performer's appearance, clothing, and environment entirely 3. Feed the depth map as the motion reference and the character sheet as the identity reference- two separate inputs doing two separate jobs, not one input trying to do both 5. Let the depth map carry only spatial movement -the model receives body position and momentum with no competing information about who's moving or what they look like 6. Keep the character and motion inputs isolated throughout - the moment you mix appearance data into the motion reference, the model starts negotiating between two identities Why this works • Raw footage passes the model everything at once- performer, wardrobe, room, lighting -and the choreography competes with all of it for attention • A depth map is pure spatial information, so the only thing left to transfer is movement • Separating identity from motion means the character can stay locked while the dance stays accurate - normally you're trading one for the other • The accuracy gain isn't the model getting better, it's the model getting fewer decisions to make Use cases: ⁃ Dance and choreography transfer onto original characters ⁃ Motion capture-style workflows without motion capture ⁃ Any sequence where a specific movement needs to survive intact ⁃ Character showcase content built on existing performance footage The character sheet answers who's dancing. The depth map answers how - and keeping those two questions separate is the whole trick.

Nexlow

84,925 Aufrufe • vor 24 Tagen