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RIP Ken Burns effect? Post camera moves will never be the same. Convert and image or video into a 3D scene and animate a virtual camera to create a new move. Camera control by Moonvalley

Paul Trillo

15,017 subscribers

13,716 次观看 • 11 个月前 •via X (Twitter)

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This tool is insane. Upload any image. Move camera in 3D space. And get a completely new camera angle 🤯 Also it’s free! 👇

This tool is insane. Upload any image. Move camera in 3D space. And get a completely new camera angle 🤯 Also it’s free! 👇

Framer 🇱🇹

986,144 次观看 • 4 个月前

Super excited to announce our new work: Synthesizing Moving People with 3D Control (3DHM)💡 Why is 3DHM unique? With 3D Control, 3DHM can animate a 𝗿𝗮𝗻𝗱𝗼𝗺 human photo with 𝗮𝗻𝘆 poses in a 𝟯𝟲𝟬-𝗱𝗲𝗴𝗿𝗲𝗲 camera view and 𝗮𝗻𝘆 camera azimuths from 𝗮𝗻𝘆 video!

Super excited to announce our new work: Synthesizing Moving People with 3D Control (3DHM)💡 Why is 3DHM unique? With 3D Control, 3DHM can animate a 𝗿𝗮𝗻𝗱𝗼𝗺 human photo with 𝗮𝗻𝘆 poses in a 𝟯𝟲𝟬-𝗱𝗲𝗴𝗿𝗲𝗲 camera view and 𝗮𝗻𝘆 camera azimuths from 𝗮𝗻𝘆 video!

Boyi Li

74,471 次观看 • 2 年前

ProjectAlpha22 🏳️‍🌈 I hand animate it while referencing the clip, and for the camera, I have the clip for the shot in the scene camera, and I do a really silly thing where I place the blender cursor on a defined point in the image, and rotate the camera to keep the image in that "spot"

ProjectAlpha22 🏳️‍🌈 I hand animate it while referencing the clip, and for the camera, I have the clip for the shot in the scene camera, and I do a really silly thing where I place the blender cursor on a defined point in the image, and rotate the camera to keep the image in that "spot"

ummwell

11,107 次观看 • 1 年前

This is wild. Every filmmaker needs to try this hybrid AI workflow for precision camera control: 1) Block out your camera in Blender to create a motion reference and animate the camera move 2) Generate your start frame in Midjourney to match the pose and composition 3) Feed both to Seedance It tracks the move almost exactly. This is the most powerful hybrid pipeline I've tried yet.

This is wild. Every filmmaker needs to try this hybrid AI workflow for precision camera control: 1) Block out your camera in Blender to create a motion reference and animate the camera move 2) Generate your start frame in Midjourney to match the pose and composition 3) Feed both to Seedance It tracks the move almost exactly. This is the most powerful hybrid pipeline I've tried yet.

Reid Hannaford

69,425 次观看 • 9 天前

🚨 This is wild Higgsfield just launched Canvas, a full image-to-video design suite Edit ANY image and turn it into a living, speaking video with Camera moves, VFX, and Avatars Fashion, ads, memes, faceless brands, all changed forever. See what’s new : 👇

🚨 This is wild Higgsfield just launched Canvas, a full image-to-video design suite Edit ANY image and turn it into a living, speaking video with Camera moves, VFX, and Avatars Fashion, ads, memes, faceless brands, all changed forever. See what’s new : 👇

ZOYA ✪

36,930 次观看 • 1 年前

Seedance 2.0 Prompt Share Today's camera technique: Motivated Continuous Camera Move A filmmaking technique frequently used by directors like Steven Spielberg, where the camera moves continuously and every shift in direction is motivated by action within the scene. Instead of cutting between shots, the camera naturally redirects its focus as new subjects enter the frame. You can find the prompt below 👇 Seedance 2.0 on Martini Art AI

Seedance 2.0 Prompt Share Today's camera technique: Motivated Continuous Camera Move A filmmaking technique frequently used by directors like Steven Spielberg, where the camera moves continuously and every shift in direction is motivated by action within the scene. Instead of cutting between shots, the camera naturally redirects its focus as new subjects enter the frame. You can find the prompt below 👇 Seedance 2.0 on Martini Art AI

Kōda

155,365 次观看 • 3 个月前

I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera..... The Camera:

I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera, I don't need a new camera..... The Camera:

Alex Aperios

24,743 次观看 • 1 年前

I can't believe this actually works 🤯 I drew a few random red arrows on an image. Seedance 2.0 on Higgsfield understood exactly how I wanted the camera to move. And turned it into a cinematic flythrough. No timeline. No camera controls. Just vibes and red scribbles. What a time to be a creator.

I can't believe this actually works 🤯 I drew a few random red arrows on an image. Seedance 2.0 on Higgsfield understood exactly how I wanted the camera to move. And turned it into a cinematic flythrough. No timeline. No camera controls. Just vibes and red scribbles. What a time to be a creator.

Pierrick Chevallier | IA

23,910 次观看 • 23 天前

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

MrNeRF

52,801 次观看 • 1 年前

Finally getting around to doing something marginally useful. Quickly putting together a small video for some one. And testing new camera out. I like the camera! I will be making a full video on the tricorder projects SOOOON!

Finally getting around to doing something marginally useful. Quickly putting together a small video for some one. And testing new camera out. I like the camera! I will be making a full video on the tricorder projects SOOOON!

MD-Builds 🏳️‍🌈🇪🇺🇵🇸

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Full creative and camera control using Runway V2V with first frame and a 3D model.

Full creative and camera control using Runway V2V with first frame and a 3D model.

Cristóbal Valenzuela

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One of the Super Meat Boy 3D prototype levels. Our first test with a fixed camera angle. No 45° angles and weird camera movement. Super motion-sickness inducing, hard to control…but it led us to the final camera setup.

One of the Super Meat Boy 3D prototype levels. Our first test with a fixed camera angle. No 45° angles and weird camera movement. Super motion-sickness inducing, hard to control…but it led us to the final camera setup.

Sluggerfly

111,326 次观看 • 4 个月前

Second test using the nerfstudio and Blender pipeline. Same scene as the previous video but now using a handheld virtual camera - nearly infinite POV options!. I've also resolved the issues I had in the 3D scene. cc Dpt. #AI #NeRF #nerfacto #neuralrendering #b3d

Second test using the nerfstudio and Blender pipeline. Same scene as the previous video but now using a handheld virtual camera - nearly infinite POV options!. I've also resolved the issues I had in the 3D scene. cc Dpt. #AI #NeRF #nerfacto #neuralrendering #b3d

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Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”

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These new AI models are so good! Dreamina AI dropped Image 3.0 and Video 3.0 and now you'll have: · no more morphing · control over the camera · everything's into place · smart image reference Prompts, comparisons and a quick how-to guide in this thread 🧵👇

These new AI models are so good! Dreamina AI dropped Image 3.0 and Video 3.0 and now you'll have: · no more morphing · control over the camera · everything's into place · smart image reference Prompts, comparisons and a quick how-to guide in this thread 🧵👇

TechHalla

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"I tried to do a cool move for the e! shot but I was a little stoned and the camera moves fast and like an alien arm"

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I created a full 15s 3D animated short from a storyboard GPT Image 2 built the full storyboard sheet: characters, shots, camera moves, timing and visual direction Then Seedance 2.0 turned it into animation All inside Leonardo Prompts below ⤵️

I created a full 15s 3D animated short from a storyboard GPT Image 2 built the full storyboard sheet: characters, shots, camera moves, timing and visual direction Then Seedance 2.0 turned it into animation All inside Leonardo Prompts below ⤵️

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Here's a breakdown of how I animated this action shot! The character rigs are parented to the camera, so I animate by eyeballing the perspective I want and then I animate the camera movement after I'm happy with how it looks owob

Here's a breakdown of how I animated this action shot! The character rigs are parented to the camera, so I animate by eyeballing the perspective I want and then I animate the camera movement after I'm happy with how it looks owob

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