Video to 3D Memory (MiDAS v3.1 + #glslViewer +

Minecraft 3D generation now at the highest quality ever,... built using fal ⛏️ Text → Image (nano-banana-pro) → 3D mesh (Hunyuan 3D v3.1) → Voxelize → Texture mapping → Minecraft structure!show more

Turn any webpage into a museum! 🏛️ Made this... Chrome extension that uses Hunyuan 3D v3.1 on fal to turn any image into a 3D model, and three.js for the interactive viewershow more

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Wuthering Waves V3.1 New official ad :) #WutheringWaves #WuWa... #鳴潮 #WuWaCollection #WuWaAnniversaryshow more

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The context size of video world models is only... a few frames. Like a human with severe memory loss! We design a long-term memory for world models based on explicit 3D representations inspired by the human mind. This enables long-term consistency. 1/3show more

MIT researchers taught a robot dog to perceive a... 3D world using Neural Volumetric Memory (NVM). This technique lets the bot climb stairs, step over gaps & run autonomously w/a single neural network. Paper: Video: w/UC San Diegoshow more

Lightplane Highly-Scalable Components for Neural 3D Fields Contemporary 3D... research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are memory-intensive, posing ashow more

LGTM from Apple: 4K feed-forward 3D Gaussian Splatting. instant... 4K 3D scenes without massive GPUs.. - predicts a few lightweight 3D shapes, wraps them in ultra-high-res 2D textures. - low Memory usage You take two normal photos of a room. Instantly walk around it in flawless 3D.show more

Yu et al., "MosaicMem: Hybrid Spatial Memory for Controllable... Video World Models" A patch-based spatial memory that you raster into views + glues to make things work.show 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

I always thought camera pose estimation is necessary for... 3D reconstruction, until Zequn and Stephen proved me wrong! Introducing PreF3R, purely feed-forward 3D Gaussian Splatting without any intermediate pose estimation and COLMAP initialization. Video in, 3D Gaussians and novel view rendering out. Key technique: spatial memory network from Spann3R and Gaussian head supervised by pointmap loss plus photometric loss. See more at:show more

A lot of work over the weekend: LYGIA: cmake/python... bundle script for C++ VERA v1.1.0: - support for gsplats - LYGIA bundle to stream line default shaders - better camera interactions GlslViewer v3.5.1: support for gsplats and native lygia supportshow more

I don’t have the BRAM for a depth buffer... so it’s time to get the memory controller up and running for this fjord torus. 100% FPGA logic 3D pipeline, no CPU.show more

Doing anything but contacting his daughter #Fortnite #Midas