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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/damo-cv/transreid
https://github.com/damo-nlp-sg/inf-clip
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
https://github.com/danielenricocahall/Keras-Weighted-Hausdorff-Distance-Loss
https://github.com/danielgordon10/re3-tensorflow
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/danijorgesantos/detectcars
https://github.com/dannofield/CarND-Extended-Kalman-Filter
No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs
https://github.com/daovietanhuet/ContourDetection
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
https://github.com/darrishabh/coviprox
https://github.com/darshans0200/YOLOTest
https://github.com/datacrisis/BOBBY2
https://github.com/daveboat/pytorch_focal_loss
https://github.com/daveredrum/ScanRefer
ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
https://github.com/david8862/keras-YOLOv3-model-set
https://github.com/davidpaulius/foon_api
Functional Object-Oriented Network: Construction & Expansion
https://github.com/daxiapazi/faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/dayfixer/darknet-comment
https://github.com/dbtmpl/Solving-Visual-Object-Ambiguities-when-Pointing
Solving Visual Object Ambiguities when Pointing: An Unsupervised Learning Approach
https://github.com/dc17540/darknet
https://github.com/debidatta/syndata-generation
Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
https://github.com/dec880126/Self-driving-with-YOLO
https://github.com/dec880126/YOLOv4-Self-driving
https://github.com/deeplearnproject/darknet
https://github.com/deepmind/deepmind-research/tree/master/transporter
Unsupervised Learning of Object Keypoints for Perception and Control
https://github.com/delixing/Data-Augmentation
https://github.com/delldu/MaskRCNN
https://github.com/delmalih/MIAS-mammography-obj-detection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/deolipankaj/Stone_Detection_MRCNN
https://github.com/destinyls/SMOKE
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
https://github.com/detectRecog/PointTrack
PointTrack++ for Effective Online Multi-Object Tracking and Segmentation
https://github.com/detectionteamucas/retinanet_tensorflow
https://github.com/developer0hye/PicoDet-Backbone
PP-PicoDet: A Better Real-Time Object Detector on Mobile Devices
https://github.com/developer0hye/Simple-PyTorch-Deformable-Convolution-v2
https://github.com/devsoft123/fast-cnn
https://github.com/dgriffiths3/finding-your-center
Finding Your (3D) Center: 3D Object Detection Using a Learned Loss
https://github.com/dheerajpreddy/CenterNet-without-DCN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.