JunjH

Revisiting_Single_Depth_Estimation

official implementation of "Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries"

Visualizing-CNNs-for-monocular-depth-estimation

official implementation of "Visualization of Convolutional Neural Networks for Monocular Depth Estimation"

Boosting-Light-Weight-Depth-Estimation

Official implementation of "Boosting Light-Weight Depth Estimation Via Knowledge Distillation"

Lifelong-MonoDepth

About official Pytorch implementation of "Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth Estimation

Semantic-Graph-based--global-Localization

Semantic graph based global localization for multi-robot map fusion.

CompletionFormer

[CVPR2023] CompletionFormer: Depth Completion with Convolutions and Vision Transformers

continual-learning

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

EfficientLPS

PyTorch code for training EfficientLPS for LiDAR panoptic segmentation. https://rl.uni-freiburg.de/research/lidar-panoptic

Elastic-Weight-Consolidation

This is an implementation of Elastic Weight Consolidation algorithm introduced in Overcoming catastrophic forgetting in neural networks.

ExtInfoMax

Codes for reproducing results in the paper "Extending information maximization from a rate-distortion perspective"

fs-map-project

MISO_connection

Algorithms for the connection planning problem of configurations composed of MISO modules, such as IM and TBB used in the article "Auto-Optimizing Connection Planning Method for Chain-Type Modular Self-Reconfiguration Robots"

NeuralCoMapping

[CVPR 2022] Multi-Robot Active Mapping via Neural Bipartite Graph Matching.

PLNet

Code for PLNet: Plane and Line Priors for Unsupervised Indoor Depth Estimation

JunjH.github.io

MS2-MultiSpectralStereoDataset

This is the official GitHub page of the Multi-Spectral Stereo (MS2) dataset described in CVPR 2023 paper.