Pinned Repositories
3D-Multi-Object-Detection-and-Tracking
Multi-Object Detection and Tracking for Autonomous Driving / Robot Perception
AB3DMOT
(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"
AdaBins
Official implementation of Adabins: Depth Estimation using adaptive bins
AdaptConfByteTrack
Source code for paper "Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking"
AutowareArchitectureProposal.proj
This is the source code of the feasibility study for Autoware architecture proposal.
Awesome-Multimodal-Object-Tracking
A personal investigative project to track the latest progress in the field of multi-modal object tracking.
awesome-multiple-object-tracking
Resources for Multiple Object Tracking (MOT)
Awesome-Point-Clouds
Awesome paper/code for point clouds with deep learning methods in detection and tracking
Awesome-Trajectory-Motion-Prediction-Papers
BEVCar
Camera-Radar Fusion for BEV Map and Object Segmentation
minho8849's Repositories
minho8849/3D-Multi-Object-Detection-and-Tracking
Multi-Object Detection and Tracking for Autonomous Driving / Robot Perception
minho8849/AdaptConfByteTrack
Source code for paper "Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking"
minho8849/Awesome-Multimodal-Object-Tracking
A personal investigative project to track the latest progress in the field of multi-modal object tracking.
minho8849/BEVCar
Camera-Radar Fusion for BEV Map and Object Segmentation
minho8849/mv-glmb-ab
This is the official Python and C++ implementation repository for Information Fusion paper entitled "Track Initialization and Re-Identification for 3D Multi-View Multi-Object Tracking" (MV-GLMB-AB (Multiview GLMB-Adaptive Birth).
minho8849/CoDA_NeurIPS2023
Official code for NeurIPS2023 paper: CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection
minho8849/CodeFormer-NIPS22-
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
minho8849/CVPR-2023-Papers
CVPR 2023 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. A star in the development of visual intelligence!
minho8849/DepthMOT
minho8849/EchoTrack
EchoTrack: Auditory Referring Multi-Object Tracking for Autonomous Driving
minho8849/FocalFormer3D-ICCV23-
Official PyTorch implementation of FocalFormer3D [ICCV 2023]
minho8849/HIT
Hierarchical IoU Tracking based on Interval
minho8849/LaMOT
minho8849/LG-MOT
Multi-Granularity Language-Guided Multi-Object Tracking
minho8849/LIMOT
A Tightly-Coupled System for LiDAR-Inertial Odometry and Multi-Object Tracking.
minho8849/MeMOTR
[ICCV 2023] MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Tracking
minho8849/MFNet
minho8849/MMF-Net
The source code of "Material-Guided Multi-View Fusion Network for Hyperspectral Object Tracking".
minho8849/MultiCorrupt
MultiCorrupt: A benchmark for robust multi-modal 3D object detection, evaluating LiDAR-Camera fusion models in autonomous driving. Includes diverse corruption types (e.g., misalignment, miscalibration, weather) and severity levels. Assess model performance under challenging conditions.
minho8849/OpenLane-V2
[NeurIPS 2023 Track Datasets and Benchmarks] OpenLane-V2: The First Perception and Reasoning Benchmark for Road Driving
minho8849/path-consistency
minho8849/PNAS-MOT
RAL paper: PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search
minho8849/RaTrack
[ICRA2024] RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
minho8849/Robo3D-ICCV23-
[ICCV'23] Robo3D: Towards Robust and Reliable 3D Perception against Corruptions
minho8849/SDSTrack
[CVPR 2024] SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking
minho8849/SimD
minho8849/SparseTrack
minho8849/TrackTacular
minho8849/Trajectory-Long-tail-Distribution-for-MOT
CVPR 2024
minho8849/UniAD
[CVPR 2023 Best Paper] Planning-oriented Autonomous Driving