KMS-TEAM's repositories
superpoint_transformer
Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"
awesome-3d-reconstruction-papers
A collection of 3D reconstruction papers in the deep learning era.
awesome-NeRF
A curated list of awesome neural radiance fields papers
ByteTrack
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
google-research
Google Research
NeRF-SLAM
NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields. https://arxiv.org/abs/2210.13641 + Sigma-Fusion: Probabilistic Volumetric Fusion for Dense Monocular SLAM https://arxiv.org/abs/2210.01276
XTDrone
UAV Simulation Platform based on PX4, ROS and Gazebo
AI-Scientist
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Applied-Deep-Learning
Applied Deep Learning Course
Awesome-3D-Object-Detection-for-Autonomous-Driving
3D Object Detection for Autonomous Driving: A Comprehensive Survey (IJCV 2023)
awesome-kan
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.
awesome-multiple-object-tracking
Resources for Multiple Object Tracking (MOT)
Awesome-Vision-Attentions
Summary of related papers on visual attention. Related code will be released based on Jittor gradually.
CVPR2023-Papers-with-Code
CVPR 2023
GNNPapers
Must-read papers on graph neural networks (GNN)
ICRA-2022-SLAM-paper-list
Unofficial ICRA 2022 SLAM paper list
Image-Matching-Paper-List
A personal list of papers and resources of image matching and pose estimation, including perspective images and panoramas.
Lightning-NeRF
[ICRA 2024] Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving
LTSLAM
You can learn slam step by step，there are lot of tutorials
ML-Papers-Explained
Explanation to key concepts in ML
ROS-LLM
ROS-LLM is a framework designed for embodied intelligence applications in ROS. It allows natural language interactions and leverages Large Language Models (LLMs) for decision-making and robot control. With an easy configuration process, this framework allows for swift integration, enabling your robot to operate with it in as little as ten minutes.
Transformer-in-Computer-Vision
A paper list of some recent Transformer-based CV works.