Bai et al., "Positional Encoding Field" Make your RoPE... encoding 3D by including a z axis, then manipulate your image by simply manipulating your positional encoding in 3D --> novel view synthesis. Neat idea.show more

Astra can make some cool spectrogram art, encoding an... entire image into audio.show more

MIMO aka VIGGLE on steroids can create controllable character... videos from a single image! It allows users to animate characters with complex motions in real-world scenes by encoding 2D videos into 3D spatial codes for flexible control. Links ⬇️show more

Discover the right 3D Geometric Foundation Model for your... task—whether it’s stereo matching, multi-view depth estimation, video depth, pose estimation, semantic understanding, or novel view synthesis. Explore more insights in our #E3DBench #FoundationModel #3D #GaussianSplatting. Project Webpage:show more

Meta's Segment Anything Model (SAM) can now run in... your browser w/ WebGPU (+ fp16), meaning up to 8x faster image encoding (10s → 1.25s)! 🤯⚡️ Video is not sped up! Everything runs 100% locally thanks to 🤗 Transformers.js and onnxruntime-web! 🔗 Demo:show more

[1/8] Drawing → 3D render with Gemini 2.0 image... generation… by Dev Valladares + me 👇🧵Make your own at the link belowshow more

3D generation now down to 30s (was 5+ minutes... before) using Z-Image T2I --> SAM-3D Image to 3D ⛏️show more

LeRobot can now see in 3D 👀🤖 Depth cameras... feed straight into training data end-to-end in v0.6.0: 12-bit precision preserved through encoding, or fully lossless raw storage if you'd rather skip compression altogether. Same release also opens up every video encoding parameter for RGB, plus a live benchmark leaderboard to help you tune it. This exact depth pipeline powers Stanford Vision and Learning Lab's BEHAVIOR-1K 2026 dataset: 20,000 simulated manipulation episodes, depth included. More on how it works below:show more

one 2d photo --> 3d gaussian splat quick test... with Echo-2 by SpAItial -- these 3d scene generation models are getting better! already at a sufficient quality to serve as a virtual set / backdrop in your 3d tool of choiceshow more

🌐 N4E encoding exclusivity. decoding value. crafted for those... who move different. built for crypto natives by natives. because true luxury isn't just appearance - it's a mindset. precision in every stitch. rebellion in every thread. not for everyone.show more

From satellite view to a real 3D model on... your wall.show more

From flat image to animated 3D models in Spaces... → Generate 3D models from an image or a prompt → Retexture, remesh, convert and UV unwrap on the canvas → Auto-rig your characters and apply animations → Snapshot any model into your image or video workflow Now on Magnificshow more

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.show more

Have you 3D printed your free Walrus yet? 🦭... This ain’t just a file. It’s a symbol of the open manufacturing movement. A FREE 3D-printed drop—powered by your clicks, backed by the 3DOS DePIN army. Claim yours now →show more

🎶Time to start NeRFing audio. Introducing NVAS3D for novel... acoustic synthesis in 3D scenes. Watch with AirPods. arxiv: code:show more

Combining the explicit control of 3D software with the... creativity of generative AI models is a promising yet underrated workflow. Build your 3D scenes procedurally by describing them in natural language, then take them all the way with your image & video models of choice. Tools like intangible are built around such a workflow so you don't need to duct-tape apps together. Pretty cool!show more

This is your sign to make a 3d animations Tiktok

The way you get 3D shoulders is by developing... your side and rear delts, not your front delts!show more

Introduction to Positional Play | Concept 1⃣1⃣ - Through... Circulation and Penetration, the Team Travels up the Field Together. Session Idea - Animations ⬇️show more

Next version of Super ZSNES is going to have... a 3D Layers view mode that lets you manipulate the camera view and check out the various layers in 3D perspective mode.show more