https://github.com/canerozer/qct
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/canturan10/satellighte
https://github.com/caojoshua/Plastic-Recyclability
https://github.com/caoquan95/6D-pose-project
DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion
https://github.com/capstone-w3/trash_parent_repo
https://github.com/captaindario/dakanji-single-kanji-recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/cardwing/codes-for-pvkd
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds
https://github.com/carinanorre/Brain-Tumour-Segmentation-Dissertation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/carolchenyx/MobilenetXT-tensorflow
Rethinking Bottleneck Structure for Efficient Mobile Network Design
https://github.com/carterprice2/Deep_Learning_project
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
https://github.com/casiopa/Madrid_Rooftops
https://github.com/castorini/deebert
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/castorini/earlyexiting-monobert
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/catalpaaa/demansia
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
https://github.com/cattidea/VinVL-Paddle
VinVL: Revisiting Visual Representations in Vision-Language Models
https://github.com/cavedunissin/deeplearning_robot_jetson_nano
https://github.com/ccc013/DeepLearning_Notes
https://github.com/ccchang1023/maskrcnn-benchmark
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free
https://github.com/cdluminate/advrank
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cdluminate/advrank-pub
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cdoersch/deepcontext
Data-dependent Initializations of Convolutional Neural Networks
https://github.com/cds-mipt/cds-tracking
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/cedricpicron/detseg
https://github.com/ceesem/refid2bib
https://github.com/celinechanny/FV-UPatches
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/cersar/3D_detection
https://github.com/cfdoge/w9ai
https://github.com/cfreshgirl/hardnet
https://github.com/cftang0827/human_recognition
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/cftang0827/pedestrian-detection-ssdlite
Rich feature hierarchies for accurate object detection and semantic segmentation
https://github.com/cftang0827/pedestrian_detection_ssdlite
Rich feature hierarchies for accurate object detection and semantic segmentation
https://github.com/cftang0827/pedestrian_recognition
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/cg1177/dcan
BasicTAD: an Astounding RGB-Only Baseline for Temporal Action Detection
https://github.com/cgebbe/kaggle_pku-autonomous-driving
MnasNet: Platform-Aware Neural Architecture Search for Mobile
https://github.com/chainer/chainercv
https://github.com/chaitravi-ce/Edge-Detection-Using-ML
Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.