35 skills found · Page 1 of 2
baegwangbin / DSINE[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation
Stable-X / StableNormal[SIGGRAPH Asia 2024 (Journal Track)] StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal
hlwang1124 / SNE RoadSegSNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
baegwangbin / Surface Normal Uncertainty[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
DrSleep / Multi Task RefinenetMulti-Task (Joint Segmentation / Depth / Surface Normas) Real-Time Light-Weight RefineNet
USTCPCS / CVPR2018 AttentionContext Encoding for Semantic Segmentation MegaDepth: Learning Single-View Depth Prediction from Internet Photos LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume On the Robustness of Semantic Segmentation Models to Adversarial Attacks SPLATNet: Sparse Lattice Networks for Point Cloud Processing Left-Right Comparative Recurrent Model for Stereo Matching Enhancing the Spatial Resolution of Stereo Images using a Parallax Prior Unsupervised CCA Discovering Point Lights with Intensity Distance Fields CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation Learning a Discriminative Feature Network for Semantic Segmentation Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation Unsupervised Deep Generative Adversarial Hashing Network Monocular Relative Depth Perception with Web Stereo Data Supervision Single Image Reflection Separation with Perceptual Losses Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains EPINET: A Fully-Convolutional Neural Network for Light Field Depth Estimation by Using Epipolar Geometry FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds Decorrelated Batch Normalization Unsupervised Learning of Depth and Egomotion from Monocular Video Using 3D Geometric Constraints PU-Net: Point Cloud Upsampling Network Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Tell Me Where To Look: Guided Attention Inference Network Residual Dense Network for Image Super-Resolution Reflection Removal for Large-Scale 3D Point Clouds PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image Fully Convolutional Adaptation Networks for Semantic Segmentation CRRN: Multi-Scale Guided Concurrent Reflection Removal Network DenseASPP: Densely Connected Networks for Semantic Segmentation SGAN: An Alternative Training of Generative Adversarial Networks Multi-Agent Diverse Generative Adversarial Networks Robust Depth Estimation from Auto Bracketed Images AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation DeepMVS: Learning Multi-View Stereopsis GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation Single-Image Depth Estimation Based on Fourier Domain Analysis Single View Stereo Matching Pyramid Stereo Matching Network A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation Image Correction via Deep Reciprocating HDR Transformation Occlusion Aware Unsupervised Learning of Optical Flow PAD-Net: Multi-Tasks Guided Prediciton-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing Surface Networks Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation TextureGAN: Controlling Deep Image Synthesis with Texture Patches Aperture Supervision for Monocular Depth Estimation Two-Stream Convolutional Networks for Dynamic Texture Synthesis Unsupervised Learning of Single View Depth Estimation and Visual Odometry with Deep Feature Reconstruction Left/Right Asymmetric Layer Skippable Networks Learning to See in the Dark
xjqi / GeoNetGeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation
ruirangerfan / Three Filters To NormalThree-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21)
bhpfelix / MTLNAS[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
jzengust / RGBD2NormalCode for Deep Surface Normal Estimation with Hierarchical RGB-D Fusion (CVPR2019)
DrSleep / DenseTorchAn easy-to-use wrapper for work with dense per-pixel tasks in PyTorch (including multi-task learning)
yindaz / Surface Normal3D surface normal estimation from a single image
OllieBoyne / FOUNDOfficial code for FOUND: Foot Optimisation with Uncertain Normals for Surface Deformation using Synthetic Data
blackjack2015 / IRSIRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation
xxlong0 / ASNDepth[ICCV 2021] Depth estimation with adaptive surface normal constraint
LeoQLi / HSurf NetHSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces
dfan / Single Image Surface Normal EstimationPyTorch implementation of the hourglass architecture proposed in "Single-Image Depth Perception in the Wild" by Chen, et al. in NIPS 2016. Adapted for surface normal estimation instead of relative depth estimation.
MMehdiMousavi / AIPlaygroundA virtual environment that allows changing isolated features in the image
nnaisense / Deep Iterative Surface Normal EstimationCode repository for our paper: Deep Iterative Surface Normal Estimation
xiaolonw / Caffe 3dnormalsurface normal estimation (CVPR 2015)
