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reshooting a video from a camera that was never there 📹 This LTX-2.3 IC-LoRA re-renders real footage from a NEW angle - same scene, same action, different camera. Pick "far to the left, higher, further" and it just… moves Cooked by Cseti 🧑‍🍳 try it live on Hugging Face: ▶️

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17,074 görüntüleme • 1 ay önce •via X (Twitter)

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LTX 2.3 is now live on Krea. this video model generates for 1/10th the cost of other top models and can learn any style or character - just upload some references and train a lora try it now 👇
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LTX 2.3 is now live on Krea. this video model generates for 1/10th the cost of other top models and can learn any style or character - just upload some references and train a lora try it now 👇

Krea

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No reshoot required. Our new Clean Plate IC-LoRA for LTX-2.3 removes people, pedestrians, and vehicles from a clip and rebuilds the empty background behind them. 🎬 Full-frame subject removal, no mask required 🏗️ Keeps architecture, ground markings & foliage intact ⚙️ Runs as a video-to-video LoRA on ComfyUI
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No reshoot required. Our new Clean Plate IC-LoRA for LTX-2.3 removes people, pedestrians, and vehicles from a clip and rebuilds the empty background behind them. 🎬 Full-frame subject removal, no mask required 🏗️ Keeps architecture, ground markings & foliage intact ⚙️ Runs as a video-to-video LoRA on ComfyUI

LTX.io

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Split-screen test on Flux 3! Prompt : Split-screen video showing the same real-time action from two different camera angles. The screen is divided vertically into two equal halves. On the left side, show a static, wide overhead view from a ceiling-mounted camera in the back corner of the room. The full room layout is visible: a couch, coffee table, rug, bookshelves, and a tall shelf near the wall. The cat is perched on top of the shelf. At the 2-second mark, it suddenly jumps, flips mid-air above the furniture, and lands gracefully on the coffee table. On the right side, show the same action in perfect sync from a side, eye-level camera placed low beside the couch. The view includes the shelf, the space between, and the coffee table. The camera follows the cat’s leap, capturing body motion, twist, and landing.Both sides must be precisely synchronized, showing the exact same event from different angles with consistent lighting, physics, and timing.
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Split-screen test on Flux 3! Prompt : Split-screen video showing the same real-time action from two different camera angles. The screen is divided vertically into two equal halves. On the left side, show a static, wide overhead view from a ceiling-mounted camera in the back corner of the room. The full room layout is visible: a couch, coffee table, rug, bookshelves, and a tall shelf near the wall. The cat is perched on top of the shelf. At the 2-second mark, it suddenly jumps, flips mid-air above the furniture, and lands gracefully on the coffee table. On the right side, show the same action in perfect sync from a side, eye-level camera placed low beside the couch. The view includes the shelf, the space between, and the coffee table. The camera follows the cat’s leap, capturing body motion, twist, and landing.Both sides must be precisely synchronized, showing the exact same event from different angles with consistent lighting, physics, and timing.

Umesh

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Always wanted to try combining my paper with NCA, and turns out this approach is a perfect starting point It decouples grid with rules from rendering by using SIREN as a decoder, so I just replaced it with SAD Same rules, different way to render them in higher resolution
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Always wanted to try combining my paper with NCA, and turns out this approach is a perfect starting point It decouples grid with rules from rendering by using SIREN as a decoder, so I just replaced it with SAD Same rules, different way to render them in higher resolution

Lucky Iyinbor

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These two Muslim men are a couple showing affection on camera. In the societies they come from, the same relationship has been punished by throwing men off rooftops. Illegal immigration does not only move bodies. It moves the law, the shame, and the violence that travel with them. Give it a few short years and this will not stay a foreign video. It will be the argument on your street and in your neighborhood.
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These two Muslim men are a couple showing affection on camera. In the societies they come from, the same relationship has been punished by throwing men off rooftops. Illegal immigration does not only move bodies. It moves the law, the shame, and the violence that travel with them. Give it a few short years and this will not stay a foreign video. It will be the argument on your street and in your neighborhood.

The Iranian

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New path control system in Seedance 2.0 just cooked Hollywood... - You draw the camera move by hand. - Scribble a red line across a still image - Feed it to the model and it flies the shot along that exact route. Then it erases the line so it never shows up in the footage. The marker stroke becomes the flight path. Prompts below on Unsora AI👇
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New path control system in Seedance 2.0 just cooked Hollywood... - You draw the camera move by hand. - Scribble a red line across a still image - Feed it to the model and it flies the shot along that exact route. Then it erases the line so it never shows up in the footage. The marker stroke becomes the flight path. Prompts below on Unsora AI👇

Rez Karim

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Normally, teaching a camera to recognize something new means collecting images and retraining a model. This one skips that. You just type what you want it to notice. It's called NanoOWL, built by NVIDIA for real-time, zero-shot object detection. Type "an owl," "a face yawning or bored," or "indoors or outdoors" and it finds it live on camera, no training, no labeled data. You can even nest queries, like detecting a face, then finding the eyes and mouth inside it. > needs a Jetson Orin board specifically > plus TensorRT and PyTorch set up > Real embedded-hardware territory
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Normally, teaching a camera to recognize something new means collecting images and retraining a model. This one skips that. You just type what you want it to notice. It's called NanoOWL, built by NVIDIA for real-time, zero-shot object detection. Type "an owl," "a face yawning or bored," or "indoors or outdoors" and it finds it live on camera, no training, no labeled data. You can even nest queries, like detecting a face, then finding the eyes and mouth inside it. > needs a Jetson Orin board specifically > plus TensorRT and PyTorch set up > Real embedded-hardware territory

Simplifying AI

24,811 görüntüleme • 25 gün önce

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.
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This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 görüntüleme • 4 ay önce

the members getting jealous cause jiwoong didn’t call them 😭 🧸 was it the same day you called me… 🦋 ah it’s not the same day!! It was a different day! 🐱 i never get any calls from him 🥺 🦌 me too! 🦋 there will be a day like that someday
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the members getting jealous cause jiwoong didn’t call them 😭 🧸 was it the same day you called me… 🦋 ah it’s not the same day!! It was a different day! 🐱 i never get any calls from him 🥺 🦌 me too! 🦋 there will be a day like that someday

nori✩

23,234 görüntüleme • 6 ay önce

It baffles me that this was a random glare in the camera lens and it was so good that they decided to keep it in the scene 😭 Like guys this is not edited he can just do that 😔
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It baffles me that this was a random glare in the camera lens and it was so good that they decided to keep it in the scene 😭 Like guys this is not edited he can just do that 😔

𝗞𝗮𝗿𝗺𝗮 (•̀ᴗ•́ )

27,172 görüntüleme • 1 ay önce

Video creation just changed forever 🎬🤯 With Cinema Studio by Higgsfield AI 🧩, you start from one cinematic frame and turn it into a full film-quality video. Camera moves. Mood. Lighting. Storytelling. No timelines. No keyframes. No pain. This feels less like “AI video” and more like directing a movie. Try it yourself →
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Video creation just changed forever 🎬🤯 With Cinema Studio by Higgsfield AI 🧩, you start from one cinematic frame and turn it into a full film-quality video. Camera moves. Mood. Lighting. Storytelling. No timelines. No keyframes. No pain. This feels less like “AI video” and more like directing a movie. Try it yourself →

The Ultimate AI Expert

333,424 görüntüleme • 8 ay önce

#NEIOH - "This is a camera from Sirius-Nopplia. It was sent from a large craft that is part of a Galactic Federation Fleet from a massive Mothership. The screens within the Mothership as well as all crafts are in constant control of all operatives sent to any location. This was a minor adjustment and the camera returned to the craft." Manchester Airport
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#NEIOH - "This is a camera from Sirius-Nopplia. It was sent from a large craft that is part of a Galactic Federation Fleet from a massive Mothership. The screens within the Mothership as well as all crafts are in constant control of all operatives sent to any location. This was a minor adjustment and the camera returned to the craft." Manchester Airport

Kab

181,899 görüntüleme • 1 yıl önce

SAM 3D Body turns video into motion capture, full-body 3D mesh from footage. Runs in ComfyUI, locally or on Comfy Cloud. Extract motion from a recording → bring it into Blender → control the camera → use the result with Seedance 2.5 More control over body motion and camera movement. To try this workflows, link below 👇
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SAM 3D Body turns video into motion capture, full-body 3D mesh from footage. Runs in ComfyUI, locally or on Comfy Cloud. Extract motion from a recording → bring it into Blender → control the camera → use the result with Seedance 2.5 More control over body motion and camera movement. To try this workflows, link below 👇

ComfyUI

26,080 görüntüleme • 13 gün önce

UPDATE: Charlie Kirk 🚨 Muzzle Flash: Second Shooter Location, Reflection, or Both? This video captures a flash on a window right as Charlie Kirk was shot. Let’s break this down… follow the numbers on the videos. #1. This video shows what appears to be a muzzle flash, just as Charlie is shot, leading people to believe the shooter was to Charlie’s right.. Notate the people to the left of the flash #2. This photo shows the location of the flash. Notate people to the left, on a middle-landing on a staircase. #3. This photo shows a clearer image showing both the middle-landing and the same location of the flash. It is a window. #4 . This video shows the building behind Charlie, which is a long hallway. This debunks any claims the shot came from here. — I zoom in where Charlie was — I zoom in on staircase — I zoom in on the window/flash — I zoom in on where suspected shooter was #5. I notate the flash reflection angles. — Video angle #1 notated — two reflection paths notated in relation to Video angle #1. 1. Reflection angle shows where we were told the shooter was. 2. Reflection angle shows mirrored angle, obviously where there is no reports of a shooter being in. 🔻 Final conclusion: This to me is very likely a muzzle flash reflection from a far off location. I am unsure of the reflection angle however, but this can be 100% proven if someone were to recreate the angles… maybe with a flash camera. If anyone is willing to, or has the means to do this (safely), this will either prove the shot came where the FBI said it came from, or it will prove there was a second shooter, in the direction of the mirrored angle.
0:16

UPDATE: Charlie Kirk 🚨 Muzzle Flash: Second Shooter Location, Reflection, or Both? This video captures a flash on a window right as Charlie Kirk was shot. Let’s break this down… follow the numbers on the videos. #1. This video shows what appears to be a muzzle flash, just as Charlie is shot, leading people to believe the shooter was to Charlie’s right.. Notate the people to the left of the flash #2. This photo shows the location of the flash. Notate people to the left, on a middle-landing on a staircase. #3. This photo shows a clearer image showing both the middle-landing and the same location of the flash. It is a window. #4 . This video shows the building behind Charlie, which is a long hallway. This debunks any claims the shot came from here. — I zoom in where Charlie was — I zoom in on staircase — I zoom in on the window/flash — I zoom in on where suspected shooter was #5. I notate the flash reflection angles. — Video angle #1 notated — two reflection paths notated in relation to Video angle #1. 1. Reflection angle shows where we were told the shooter was. 2. Reflection angle shows mirrored angle, obviously where there is no reports of a shooter being in. 🔻 Final conclusion: This to me is very likely a muzzle flash reflection from a far off location. I am unsure of the reflection angle however, but this can be 100% proven if someone were to recreate the angles… maybe with a flash camera. If anyone is willing to, or has the means to do this (safely), this will either prove the shot came where the FBI said it came from, or it will prove there was a second shooter, in the direction of the mirrored angle.

MJTruthUltra

10,665,164 görüntüleme • 1 yıl önce

New open source LoRA Multi-Angles I created with fal for Flux.2 🔥 Flux2.-Lora-Multi-Angles: give a camera angle in degrees → get your image from that view. To build this, I created a system that captures 72 positions from Gaussian Splatting to generate the training dataset fully automatically in a webgl viewer. ▶️ Test: 📥 Weights: Should I open source my WebGL viewer so you can train your own from gaussian splatting ?
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New open source LoRA Multi-Angles I created with fal for Flux.2 🔥 Flux2.-Lora-Multi-Angles: give a camera angle in degrees → get your image from that view. To build this, I created a system that captures 72 positions from Gaussian Splatting to generate the training dataset fully automatically in a webgl viewer. ▶️ Test: 📥 Weights: Should I open source my WebGL viewer so you can train your own from gaussian splatting ?

Lovis Odin

43,693 görüntüleme • 9 ay önce

We introduced a completely new camera angle: through the pieces, right into the face of the players. It feels magical so see the player's eyes, emotions and thought process in such an intimate way. I wish I could take photos from that angle :)
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We introduced a completely new camera angle: through the pieces, right into the face of the players. It feels magical so see the player's eyes, emotions and thought process in such an intimate way. I wish I could take photos from that angle :)

Lennart Ootes

99,626 görüntüleme • 2 yıl önce

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀
0:18

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀

🚨 AI News | TestingCatalog

12,051 görüntüleme • 1 ay önce