https://github.com/jonasannuscheit/rpdac_for_midog22
공식 코드Radial Prediction Domain Adaption Classifier for the MIDOG 2022 Challenge
Papers with Code 아카이브
Object Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jongmokkim/mix-unmix
공식 코드MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
https://github.com/jonpappalord/PassNet
공식 코드Automatic Pass Annotation from Soccer VideoStreams Based on Object Detection and LSTM
https://github.com/joshuafeinglass/vl-detector-eval
공식 코드https://github.com/joshualpf/alignsal
공식 코드https://github.com/joshualpf/dfenet
공식 코드Deep Fourier-embedded Network for Bi-modal Salient Object Detection
https://github.com/joyfang1106/mrla
공식 코드https://github.com/jozhang97/deta
공식 코드https://github.com/jp-guo/gm-transformer
공식 코드https://github.com/jsbruglie/tf-shape-detection
공식 코드Applying Domain Randomization to Synthetic Data for Object Category Detection
https://github.com/jsgyun/SLCAN
공식 코드https://github.com/jshilong/FisherPruning
공식 코드https://github.com/jshilong/SEPC
공식 코드https://github.com/jshilong/ddq
공식 코드https://github.com/jshilong/grouprcnn
공식 코드Group R-CNN for Weakly Semi-supervised Object Detection with Points
https://github.com/jsiloto/adaptive-cob
공식 코드Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation
https://github.com/jugghm/orepa_cvpr2022
공식 코드https://github.com/julian075/catalog
공식 코드CATALOG: A Camera Trap Language-guided Contrastive Learning Model
https://github.com/juliantrue/movex
공식 코드https://github.com/julimueller/disparity-sliding-window
공식 코드Disparity Sliding Window: Object Proposals From Disparity Images
https://github.com/julimueller/tl_ssd
공식 코드https://github.com/juliozhao97/efftrans_fsdet
공식 코드Exploring Effective Knowledge Transfer for Few-shot Object Detection
https://github.com/junayed/sonar-scan-dataset-with-ping-360
공식 코드https://github.com/junchen14/LoMaR
공식 코드Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction
https://github.com/junhyung-SPALab/D-Align
공식 코드https://github.com/junjie18/cmt
공식 코드Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
https://github.com/junzhang2016/NTU4DRadLM
공식 코드NTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping
https://github.com/justimyhxu/Dense-RepPoints
공식 코드Dense RepPoints: Representing Visual Objects with Dense Point Sets
https://github.com/justincdavis/cv2ext/tree/main/src/cv2ext/research/shift
공식 코드Context-aware Multi-Model Object Detection for Diversely Heterogeneous Compute Systems
https://github.com/justinkay/aldi
공식 코드Align and Distill: Unifying and Improving Domain Adaptive Object Detection
https://github.com/justlovesmile/earl
공식 코드https://github.com/jw-chae/sjtu
공식 코드https://github.com/jwhgdeu/tsbp
공식 코드https://github.com/jwliang007/ikd
공식 코드Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation
https://github.com/jwwangchn/NWD
공식 코드A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
https://github.com/jxr326/swinmcnet
공식 코드Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.