GRNetImplementation of "GRNet: Gridding Residual Network for Dense Point Cloud Completion". (Xie et al., ECCV 2020)
Stars: ✭ 239 (+455.81%)
Openmvsopen Multi-View Stereo reconstruction library
Stars: ✭ 1,842 (+4183.72%)
SASensorProcessingROS node to create pointcloud out of stereo images from the KITTI Vision Benchmark Suite
Stars: ✭ 26 (-39.53%)
PAM[TPAMI 2020] Parallax Attention for Unsupervised Stereo Correspondence Learning
Stars: ✭ 62 (+44.19%)
PandoraA stereo matching framework that will help you design your stereo matching pipeline with state of the art performances.
Stars: ✭ 31 (-27.91%)
pais-mvsMulti-view stereo image-based 3D reconstruction
Stars: ✭ 55 (+27.91%)
PatchMatchCudaThe PatchMatch stereo match algorithm implemented by CUDA.
Stars: ✭ 32 (-25.58%)
GC-Netgc-net for stereo matching by using pytorch
Stars: ✭ 80 (+86.05%)
UAV-Stereo-VisionA program for controlling a micro-UAV for obstacle detection and collision avoidance using disparity mapping
Stars: ✭ 30 (-30.23%)
BridgeDepthFlowBridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
Stars: ✭ 114 (+165.12%)
edlsm pytorchPytorch implementation for stereo matching described in the paper: Efficient Deep learning for stereo matching
Stars: ✭ 16 (-62.79%)
stereoPerform stereo matching algorithm using Direct 3D (level 9.3) on a mobile device without CUDA support.
Stars: ✭ 13 (-69.77%)
RealtimeStereoAttention-Aware Feature Aggregation for Real-time Stereo Matching on Edge Devices (ACCV, 2020)
Stars: ✭ 110 (+155.81%)
rectified-features[ECCV 2020] Single image depth prediction allows us to rectify planar surfaces in images and extract view-invariant local features for better feature matching
Stars: ✭ 57 (+32.56%)
Depth estimationDeep learning model to estimate the depth of image.
Stars: ✭ 62 (+44.19%)
CSPN monodepthUnofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network
Stars: ✭ 66 (+53.49%)
DiverseDepthThe code and data of DiverseDepth
Stars: ✭ 150 (+248.84%)
ForeSeETask-Aware Monocular Depth Estimation for 3D Object Detection, AAAI2020
Stars: ✭ 58 (+34.88%)
MonoDEVSNetOfficial PyTorch implementation of MonoDEVSNet - "Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision."
Stars: ✭ 34 (-20.93%)
temporal-depth-segmentationSource code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).
Stars: ✭ 20 (-53.49%)
SGDepth[ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance
Stars: ✭ 162 (+276.74%)
EPCDepth[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
Stars: ✭ 105 (+144.19%)
3ddfa v2The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
Stars: ✭ 1,961 (+4460.47%)
advrankAdversarial Ranking Attack and Defense, ECCV, 2020.
Stars: ✭ 19 (-55.81%)
SOLARPyTorch code for "SOLAR: Second-Order Loss and Attention for Image Retrieval". In ECCV 2020
Stars: ✭ 150 (+248.84%)
tfvaegan[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
Stars: ✭ 107 (+148.84%)
BA3UScode for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"
Stars: ✭ 31 (-27.91%)
Multimodal-Shape-Completioncode for our ECCV 2020 spotlight paper "Multimodal Shape Completion via Conditional Generative Adversarial Networks"
Stars: ✭ 73 (+69.77%)
AdvPCAdvPC: Transferable Adversarial Perturbations on 3D Point Clouds (ECCV 2020)
Stars: ✭ 35 (-18.6%)
GraphMemVOSVideo Object Segmentation with Episodic Graph Memory Networks (ECCV2020 spotlight)
Stars: ✭ 92 (+113.95%)