StringerYwh00

StringerYwh00's Stars

• IGLICT/SketchDream

  Language:Python604

• facebookresearch/audio2photoreal

  Code and dataset for photorealistic Codec Avatars driven from audio

  Language:Python2.7k262

• baaivision/See3D

  You See it, You Got it: Learning 3D Creation on Pose-Free Videos at Scale

  Language:Python42512

• tr3e/InterGen

  [IJCV 2024] InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions

  Language:Python22711

• zhenzhiwang/intercontrol

  [NeurIPS 2024] Official implementation of InterControl

  Language:Python734

• dcharatan/flowmap

  [3DV 2025] Code for "FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent" by Cameron Smith*, David Charatan*, Ayush Tewari, and Vincent Sitzmann

  Language:Python90789

• sony/genwarp

  Language:Python23620

• paintscene4d/paintscene4d.github.io

  Language:JavaScript13

• LuMen-ze/Semantic-Gesticulator-Official

  736

• m-hamza-mughal/convofusion

  Code for CVPR 2024 paper: ConvoFusion: Multi-Modal Conversational Diffusion for Co-Speech Gesture Synthesis

  Language:Python202

• MARVELOUSJI/REFRAME

  This repository is the official implementation for the paper “REFRAME: Reflective Surface Real-Time Rendering for Mobile Devices”.

  Language:Python20

• sony/NeISF

  Language:Python92

• ktiwary2/orca

  Language:Jupyter Notebook425

• ZqlwMatt/Tex4D

  Official Implementation of paper "Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models"

  Language:Python513

• KAIST-Visual-AI-Group/APAP

  The reference implementation of As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priors (CVPR 2024).

  Language:Python515

• threedle/MeshUp

  201

• threedle/TextDeformer

  Language:Python11912

• yiqun-wang/Factored-NeuS

  Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy Objects

  Language:Python131

• openhuman-ai/awesome-gesture_generation

  Awesome Gesture Generation

  1674

• wenj/GoMAvatar

  Offical codes for "GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-Mesh"

  Language:Python10711

• zju3dv/EasyMocap

  Make human motion capture easier.

  Language:Python3.8k463

• xk-huang/ema

  [Preprint 23] "Efficient Meshy Neural Fields for Animatable Human Avatars" https://arxiv.org/abs/2303.12965

  Language:Python25

• Wayne-Mai/traf_public

  Language:Python142

• chen-wl20/DreamCinema

  DreamCinema: Cinematic Transfer with Free Camera and 3D Character

  891

• gohar-malik/InterMask

  14

• xubaixinxbx/neuparam

  [ECCV'24]Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering

  Language:Python5

• fraunhoferhhi/AT-GS

  Adaptive and Temporally Consistent Gaussian Surfels for Multi-view Dynamic Reconstruction

  Language:Python251

• taconite/IntrinsicAvatar

  [CVPR 2024] IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing

  Language:Python906

• xiaobiaodu/MVGS

  MVGS: Multi-View Regulated Gaussian Splatting for Novel View Synthesis

  Language:Python1319

• apple/ml-depth-pro

  Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.

  Language:Python3.9k269