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: ▶️show more

POV: you gave AI one camera angle and it... came back with a whole film crew 😭 Close-ups. New angles. Camera moves. Same video, completely re-directed. Made on WaveSpeedshow more

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 👇show more

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 ComfyUIshow more

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.show more

THE REAL TEST IS WHAT HAPPENS WHEN SHE DISAPPEARS... At first, it looks like a normal POV clip from a crowded carnival booth: plush bears above, people moving through the frame, and a girl paying with her phone. But then she gets fully blocked twice. First by a man carrying a child, then by another group passing through the same shot. Both times, she disappears from view, and both times she returns exactly the same: same spot, same posture, same payment motion, same phone, same hand, same angle. That is where AI video usually breaks. It is easy to keep a subject stable when nothing covers them. The harder part is restoring them after a full obstruction without changing the face, hands, outfit, pose, timing or objects. Here, the scene holds. No face shift, no hand glitch, no outfit drift, no phone jump, no reset after the frame clears. And the wild part is that none of it was filmed: not the booth, not the plush toys, not the strangers crossing the camera. AI video is starting to survive the messy interruptions that make real footage feel realshow more

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 resolutionshow more

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.show more

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👇show more

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 territoryshow more

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.show more

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 somedayshow more

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 😔show more

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 →show more

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 👇show more

#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 Airportshow more

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 ?show more

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.show more

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 :)show more