https://github.com/researchmm/LightTrack
공식 코드LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Papers with Code 아카이브
Object Tracking
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Object tracking is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment. State-of-the-art methods involve fusing data from RGB and event-based cameras to produce more reliable object tracking. CNN-based models using only RGB images as input are also effective. The most popular benchmark is OTB. There are several evaluation metrics specific to object tracking, including HOTA, MOTA, IDF1, and Track-mAP.
<span style="color:grey; opacity: 0.6">( Image credit: Towards-Realtime-MOT )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/researchmm/SiamDW
공식 코드Deeper and Wider Siamese Networks for Real-Time Visual Tracking
https://github.com/researchmm/Stark
공식 코드https://github.com/researchmm/TracKit
공식 코드https://github.com/rfalque/semantic_keypoints_extraction
공식 코드Semantic keypoint extraction for scanned animals using multi-depth-camera systems
https://github.com/rfonod/geo-trax
공식 코드Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
https://github.com/risc-nyuad/siamtpntracker
공식 코드Siamese Transformer Pyramid Networks for Real-Time UAV Tracking
https://github.com/roboflow-ai/roboflow-100-benchmark
공식 코드Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark
https://github.com/roth-hex-lab/gbot
공식 코드GBOT: Graph-Based 3D Object Tracking for Augmented Reality-Assisted Assembly Guidance
https://github.com/roydenwa/efficient-cell-seg
공식 코드EfficientCellSeg: Efficient Volumetric Cell Segmentation Using Context Aware Pseudocoloring
https://github.com/royerlab/ultrack
공식 코드Large-Scale Multi-Hypotheses Cell Tracking Using Ultrametric Contours Maps
https://github.com/rozumden/DeFMO
공식 코드https://github.com/rozumden/deblatting_python
공식 코드https://github.com/rozumden/fmo-deblurring-benchmark
공식 코드https://github.com/s-shailja/ucsb_ctc
공식 코드Semi supervised segmentation and graph-based tracking of 3D nuclei in time-lapse microscopy
https://github.com/sahandha/eif
공식 코드https://github.com/samuelmurray/tracking-by-detection
공식 코드Real-Time Multiple Object Tracking - A Study on the Importance of Speed
https://github.com/sangdon/PAC-confidence-set
공식 코드PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
https://github.com/sbelharbi/tcam-wsol-video
공식 코드TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos
https://github.com/scopagroup/bactrak
공식 코드https://github.com/serycjon/WOFT
공식 코드https://github.com/shajiayu1/OmniDataComposer
공식 코드OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data Generation
https://github.com/shallowtoil/DROL
공식 코드Discriminative and Robust Online Learning for Siamese Visual Tracking
https://github.com/shanjiayao/ptt
공식 코드PTT: Point-Track-Transformer Module for 3D Single Object Tracking in Point Clouds
https://github.com/shanzard/ros-sam
공식 코드ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object
https://github.com/shengyuhao/divotrack
공식 코드https://github.com/shijieS/DMMN
공식 코드Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking
https://github.com/shijieS/OMOTDRecorder
공식 코드Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking
https://github.com/shijieS/OmniMOTDataset
공식 코드Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking
https://github.com/shijieS/SST
공식 코드https://github.com/showlab/videolisa
공식 코드One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos
https://github.com/shuheikurita/refego
공식 코드RefEgo: Referring Expression Comprehension Dataset from First-Person Perception of Ego4D
https://github.com/sianalytics/bmtt2022_sia_track
공식 코드https://github.com/siddiquemu/sct_mcta
공식 코드Tracking Passengers and Baggage Items using Multiple Overhead Cameras at Security Checkpoints
https://github.com/sisl/perceptionadaptivestresstesting
공식 코드How Do We Fail? Stress Testing Perception in Autonomous Vehicles
https://github.com/sivandoveh/iploc
공식 코드Teaching VLMs to Localize Specific Objects from In-context Examples
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.