房森 (FangSen9000)

FangSen9000

Geek Repo

Company:Rutgers University

Location:NJ, United States

Home Page:https://fangsen9000.github.io

Twitter:@SenFang01

Github PK Tool:Github PK Tool

房森's starred repositories

AnimateAnyone

Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation

magic-animate

[CVPR 2024] MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

Language:PythonLicense:BSD-3-ClauseStargazers:10396Issues:104Issues:146

Moore-AnimateAnyone

Character Animation (AnimateAnyone, Face Reenactment)

Language:PythonLicense:Apache-2.0Stargazers:3103Issues:37Issues:150

trimesh

Python library for loading and using triangular meshes.

Language:PythonLicense:MITStargazers:2963Issues:48Issues:1559

Open-AnimateAnyone

Unofficial Implementation of Animate Anyone

MusePose

MusePose: a Pose-Driven Image-to-Video Framework for Virtual Human Generation

Language:PythonLicense:NOASSERTIONStargazers:2145Issues:43Issues:64

smplify-x

Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

Language:PythonLicense:NOASSERTIONStargazers:1742Issues:67Issues:221

minimal

Minimal is a Jekyll theme for GitHub Pages

Language:SCSSLicense:CC0-1.0Stargazers:1567Issues:18Issues:73

MotionGPT

[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs

Language:PythonLicense:MITStargazers:1462Issues:47Issues:95

SMPLer-X

Official Code for "SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation"

Language:PythonLicense:NOASSERTIONStargazers:976Issues:22Issues:71

MocapNET

We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance

Language:C++License:NOASSERTIONStargazers:846Issues:36Issues:121

translate

Effortless Real-Time Sign Language Translation

Language:TypeScriptLicense:NOASSERTIONStargazers:465Issues:20Issues:135

ControlNet_Plus_Plus

Official PyTorch implementation of ECCV 2024 Paper: ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback.

Language:PythonLicense:Apache-2.0Stargazers:380Issues:11Issues:11
Language:PythonLicense:NOASSERTIONStargazers:349Issues:2Issues:53

DatasetDM

[NeurIPS2023] DatasetDM:Synthesizing Data with Perception Annotations Using Diffusion Models

world-models

Extracting spatial and temporal world models from LLMs

Language:Jupyter NotebookLicense:MITStargazers:233Issues:6Issues:4

UniHSI

[ICLR 2024 Spotlight] Unified Human-Scene Interaction via Prompted Chain-of-Contacts

UniMoCap

[Open-source Project] UniMoCap: community implementation to unify the text-motion datasets (HumanML3D, KIT-ML, and BABEL) and whole-body motion dataset (Motion-X).

Language:PythonLicense:NOASSERTIONStargazers:146Issues:5Issues:3

puppeteer

Code for "Hierarchical World Models as Visual Whole-Body Humanoid Controllers"

Language:PythonLicense:MITStargazers:143Issues:5Issues:2

FineGym

All about FineGym (CVPR 2020 Oral): models, features, data, and more... keep starring and stay tuned!

word-embeddings-for-nmt

Supplementary material for "When and Why Are Pre-trained Word Embeddings Useful for Neural Machine Translation?" at NAACL 2018

sign-language-processing.github.io

Documentation and background of sign language processing

datasets

TFDS data loaders for sign language datasets.

Sign-Language-Translator

Sign Language Translator enables the hearing impaired user to communicate efficiently in sign language, and the application will translate the same into text/speech. The user has to train the model, by recording its own sign language gestures. Internally it uses MobileNet and KNN classifier to classify the gestures.

Language:HTMLLicense:MITStargazers:34Issues:2Issues:1

clash-dashboard

clash-dashboard 最新备份,原仓库删库前一天克隆的,包含绝大部分提交记录。

Language:TypeScriptLicense:MITStargazers:32Issues:1Issues:0
Language:Jupyter NotebookStargazers:21Issues:0Issues:0

Sign-Language-Mocap-Archive

Collected Sign Language Motion Capture

License:CC0-1.0Stargazers:10Issues:1Issues:0

pose-pipelines

Pipelines to process (crop, mask, and estimate poses) sign language videos like the way described in WMT-SLT 22

Language:PythonLicense:MITStargazers:3Issues:3Issues:0

lsedataset

Spanish Sign Language dataset

Language:PythonLicense:BSD-2-ClauseStargazers:1Issues:1Issues:25
Language:HTMLStargazers:1Issues:0Issues:0