Progressive Decoder Fusion, Accepted at CoLLAs, 2022.
-
Updated
Dec 14, 2022 - Python
Progressive Decoder Fusion, Accepted at CoLLAs, 2022.
TypeScript implementation of iterative closest point (ICP) for point cloud registration
My Bachelor's Thesis Project
Normal Inference Module in PyTorch, IROS 2020
Adversarial Structure Matching for Structured Prediction Tasks
PyTorch Implementation of "NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction"
A virtual environment that allows changing isolated features in the image
Official code for FOUND: Foot Optimisation with Uncertain Normals for Surface Deformation using Synthetic Data
An easy-to-use wrapper for work with dense per-pixel tasks in PyTorch (including multi-task learning)
Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21)
[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation
Multi-Task (Joint Segmentation / Depth / Surface Normas) Real-Time Light-Weight RefineNet
SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
Add a description, image, and links to the surface-normals-estimation topic page so that developers can more easily learn about it.
To associate your repository with the surface-normals-estimation topic, visit your repo's landing page and select "manage topics."