Superpoint graphLarge-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Stars: β 533 (+133.77%)
Sota Point Cloudπ₯Deep Learning for 3D Point Clouds (IEEE TPAMI, 2020)
Stars: β 778 (+241.23%)
Involution[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
Stars: β 252 (+10.53%)
PixellibVisit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
Stars: β 327 (+43.42%)
LabelmeImage Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Stars: β 7,742 (+3295.61%)
image-segmentationMask R-CNN, FPN, LinkNet, PSPNet and UNet with multiple backbone architectures support readily available
Stars: β 62 (-72.81%)
mix3dMix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021 Oral)
Stars: β 183 (-19.74%)
FaPN[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Stars: β 173 (-24.12%)
pointnet2 semanticA pointnet++ fork, with focus on semantic segmentation of differents datasets
Stars: β 69 (-69.74%)
PazHierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.
Stars: β 131 (-42.54%)
EntityEntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
Stars: β 313 (+37.28%)
CAP augmentationCut and paste augmentation for object detection and instance segmentation
Stars: β 93 (-59.21%)
FpconvFPConv: Learning Local Flattening for Point Convolution, CVPR 2020
Stars: β 114 (-50%)
Xtreme-VisionA High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.
Stars: β 77 (-66.23%)
InstantDLInstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
Stars: β 33 (-85.53%)
ObjectNetPyTorch implementation of "Pyramid Scene Parsing Network".
Stars: β 15 (-93.42%)
Paper-NotesPaper notes in deep learning/machine learning and computer vision
Stars: β 37 (-83.77%)
Panoptic DeeplabThis is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)
Stars: β 355 (+55.7%)
Jsis3d[CVPR'19] JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds
Stars: β 144 (-36.84%)
Cylinder3dRank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
Stars: β 221 (-3.07%)
Keras UnetHelper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
Stars: β 196 (-14.04%)
PixelnetThe repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at <http://www.cs.cmu.edu/~aayushb/pixelNet/>.
Stars: β 194 (-14.91%)
SamplenetDifferentiable Point Cloud Sampling (CVPR 2020 Oral)
Stars: β 212 (-7.02%)
Kitti DatasetVisualising LIDAR data from KITTI dataset.
Stars: β 217 (-4.82%)
SarosperceptionkittiROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
Stars: β 193 (-15.35%)
LiblasC++ library and programs for reading and writing ASPRS LAS format with LiDAR data
Stars: β 211 (-7.46%)
3dgnn pytorch3D Graph Neural Networks for RGBD Semantic Segmentation
Stars: β 187 (-17.98%)
MmdetectionOpenMMLab Detection Toolbox and Benchmark
Stars: β 17,646 (+7639.47%)
Smoothly Blend Image PatchesUsing a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
Stars: β 218 (-4.39%)
FcnChainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Stars: β 211 (-7.46%)
CgnetCGNet: A Light-weight Context Guided Network for Semantic Segmentation [IEEE Transactions on Image Processing 2020]
Stars: β 186 (-18.42%)
Eye In The Sky Satellite Image Classification using semantic segmentation methods in deep learning
Stars: β 185 (-18.86%)
IntradaUnsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision (CVPR 2020 Oral)
Stars: β 211 (-7.46%)
3d PointcloudPapers and Datasets about Point Cloud.
Stars: β 179 (-21.49%)
3d Bat3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling
Stars: β 179 (-21.49%)
TorchdistillPyTorch-based modular, configuration-driven framework for knowledge distillation. π18 methods including SOTA are implemented so far. π Trained models, training logs and configurations are available for ensuring the reproducibiliy.
Stars: β 177 (-22.37%)
DisplazA hackable lidar viewer
Stars: β 177 (-22.37%)
PointnetvladPointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018
Stars: β 224 (-1.75%)
LightnetplusplusLightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
Stars: β 218 (-4.39%)
Vision3dResearch platform for 3D object detection in PyTorch.
Stars: β 177 (-22.37%)
ImgclsmobSandbox for training deep learning networks
Stars: β 2,405 (+954.82%)
MeshlabThe open source mesh processing system
Stars: β 2,619 (+1048.68%)
Solov2SOLOv2: Dynamic, Faster and Stronger, achives 39.5mAP on coco test-dev (36 epochs result)
Stars: β 174 (-23.68%)
CgalThe public CGAL repository, see the README below
Stars: β 2,825 (+1139.04%)