YigaoWang

YigaoWang's Stars

• siyandong/CoScan

  Virtual scan for Multi-Robot Collaborative Dense Scene Reconstruction.

  Language:C++316

• he-dhamo/graphto3d

  Code for ICCV 2021 paper Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes using Scene Graphs

  Language:Python5912

• uctb/UCTB

  An Open Source Spatio-Temporal Prediction Package

  Language:Python18242

• YigaoWang/UCTB

  An Open Source Spatio-Temporal Prediction Package

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• DmitryRyumin/CVPR-2023-24-Papers

  CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!

  Language:Python39528

• DmitryRyumin/ICCV-2023-Papers

  ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!

  Language:Python92542

• paulgay/VGfM

  Language:Python96

• danfeiX/scene-graph-TF-release

  "Scene Graph Generation by Iterative Message Passing" code repository

  Language:Python422130

• ShunChengWu/SceneGraphFusion

  Language:C++15826

• wffancy/3dssg

  3D scene graph generation using GCN

  Language:Python448

• ShunChengWu/3DSSG

  Language:Python13421

• 3DSSG/3DSSG.github.io

  Language:CSS101

• niessner/BundleFusion

  [Siggraph 2017] BundleFusion: Real-time Globally Consistent 3D Reconstruction using Online Surface Re-integration

  Language:C++1.5k355

• nerminsamet/seedal

  [ICCV-23] Official implementation of SeedAL for seeding active learning for 3D semantic segmentation

  Language:Python25

• ericliu859/AcmPaper

  Language:Delphi226106

• mit-han-lab/spvnas

  [ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

  Language:Python583109

• francisengelmann/PyViz3D

  PyViz3D is a web-based visualizer for 3D objects and point clouds.

  Language:Python33925

• drprojects/superpoint_transformer

  Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"

  Language:Python58675

• hewei-nju/clash-for-linux

  Linux 端使用 Clash 作为代理工具

  Language:Shell187

• KangchengLiu/Feature-Geometric-Net-FG-Net

  :fire: :muscle: FG-Net: A Fast and Accurate Framework for Large-Scale LiDAR Point Cloud Understanding

  Language:C++11712

• loicland/superpoint_graph

  Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

  Language:Python758214

• cupy/cupy

  NumPy & SciPy for GPU

  Language:Python9.4k843

• jacobgil/pytorch-grad-cam

  Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

  Language:Python10.4k1.5k

• shaofeifei11/SSDR-AL

  Active Learning for Point Cloud Semantic Segmentation via Spatial-Structural Diversity Reasoning

  Language:C++225

• hzykent/LiDAL

  Implementation of ECCV2022 paper - LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation

  Language:Python311

• tsunghan-wu/ReDAL

  🍀 Official pytorch implementation of "ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation. Wu et al. ICCV 2021."

  Language:Python4110

• nihalsid/ViewAL

  [CVPR'20] Implementation for the paper "ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation"

  Language:Python14228

• JonasSchult/Mask3D

  Mask3D predicts accurate 3D semantic instances achieving state-of-the-art on ScanNet, ScanNet200, S3DIS and STPLS3D.

  Language:Python540108

• MIT-SPARK/llm_scene_understanding

  Language:HTML745

• ScanNet/ScanNet

  Language:C1.8k348