Papers with Code 아카이브
Visual Object Tracking
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Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/saimj7/People-Counting-in-Real-Time
https://github.com/samo1petar/SSD
https://github.com/saswat0/CRVOS
https://github.com/saunack/MobileNetv2-SSD
https://github.com/scaelles/OSVOS-TensorFlow
https://github.com/scrambleegg7/ssd_prescription
https://github.com/serengil/deepface
https://github.com/sgrvinod/a-pytorch-tutorial-to-object-detection
https://github.com/shashankvkt/video_object_segmentation
https://github.com/shenyunhang/caffe-fwsl
https://github.com/shunk031/chainer-skin-lesion-detector
https://github.com/songheony/A3T
AAA: Adaptive Aggregation of Arbitrary Online Trackers with Theoretical Performance Guarantee
https://github.com/soran-ghaderi/torchebm
https://github.com/spencerkraisler/Finger-Counter
https://github.com/stevensmiley1989/MrRobot
https://github.com/sunqiangxtcsun/SSD
https://github.com/suraj-maniyar/Object-Tracking-SSD300
https://github.com/susomena/DeepSlowMotion
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking
https://github.com/taokong/RON
https://github.com/tatsuyaokunaga/Simpsons_Detection
https://github.com/tchernitski/caffe.deploy
https://github.com/tolotrasamuel/real-time-object-detection-retraining-ncs-raspberry-pi
https://github.com/toseek01/eyebird
https://github.com/tryolabs/luminoth
https://github.com/tsingqguo/AttackTracker
SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
https://github.com/tsunekoromochi/ssd
https://github.com/uvipen/ssd-pytorch
https://github.com/valentina-kustikova/dnn-object-detectors-comp
https://github.com/vandangorade/BrandLOGO_detection
https://github.com/victordibia/handtracking
https://github.com/visaVita/mmaction2
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/visiblesensors/caffe-ssd
https://github.com/vita-epfl/rock-pytorch
https://github.com/vivek20dadhich/deep-learning-object-detection
https://github.com/wangdongdut/dut-anti-uav
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.