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(CVPR 2025) Scailing Down Text Encoders of Text-to-Image Diffusion Models
Official code of "Imagine360: Immersive 360 Video Generation from Perspective Anchor"
HunyuanVideo: A Systematic Framework For Large Video Generation Model
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"
[ICLR 2025] Pyramidal Flow Matching for Efficient Video Generative Modeling
Official inference repo for FLUX.1 models
[ICCV 2025] SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Edit anything in images powered by segment-anything, ControlNet, StableDiffusion, etc. (ACM MM)
DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model. NeurIPS 2024 Spotlight.
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[ECCV 2024 Best Paper Candidate & TPAMI 2025] PointLLM: Empowering Large Language Models to Understand Point Clouds
[WACV'25 Oral] Fine-Tuning Image-Conditional Diffusion Models is Easier than You Think
[ECCV 2024 Oral] MotionDirector: Motion Customization of Text-to-Video Diffusion Models.
Modified 3D Gaussian rasterizer for latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction
Cool vision, learning, and graphics papers on Cats!
CoTracker is a model for tracking any point (pixel) on a video.
Unofficial implementation of the paper "One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing" (CVPR 2021 Oral)
[ICCV 2025] From anything to mesh like human artists. Official impl. of "MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization"
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.