https://github.com/JensBayer/transferability
공식 코드Network transferability of adversarial patches in real-time object detection
Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Jia-Research-Lab/MSAD
공식 코드Multi-Scale Aligned Distillation for Low-Resolution Detection
https://github.com/Jia-Research-Lab/ReviewKD
공식 코드https://github.com/Jia-Research-Lab/SA-AutoAug
공식 코드https://github.com/JiahuiYu/slimmable_networks
공식 코드https://github.com/JialeCao001/SipMask
공식 코드SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
https://github.com/JialianW/Forest_RCNN
공식 코드Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation
https://github.com/JialianW/GRiT
공식 코드GRiT: A Generative Region-to-text Transformer for Object Understanding
https://github.com/JialianW/TraDeS
공식 코드https://github.com/JianboGuo/network-decoupling
공식 코드Network Decoupling: From Regular to Depthwise Separable Convolutions
https://github.com/Jianf-Wang/GRCNN
공식 코드Convolutional Neural Networks with Gated Recurrent Connections
https://github.com/JiaxiHe/Image-and-Video-Dehazing
공식 코드Fast Single Image Dehazing via Multilevel Wavelet Transform based Optimization
https://github.com/JinYuanLi0012/RiVEG
공식 코드LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition
https://github.com/JingZhang617/COD-Rank-Localize-and-Segment
공식 코드Simultaneously Localize, Segment and Rank the Camouflaged Objects
https://github.com/JingZhang617/Joint_COD_SOD
공식 코드Uncertainty-aware Joint Salient Object and Camouflaged Object Detection
https://github.com/JingZhang617/Scribble_Saliency
공식 코드Weakly-Supervised Salient Object Detection via Scribble Annotations
https://github.com/JingZhang617/UCNet
공식 코드https://github.com/JingbiaoMei/BayesFTNA
공식 코드BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture
https://github.com/Jinming-Su/PurNet
공식 코드Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss
https://github.com/Jinming-Su/TSOD
공식 코드Exploring Driving-aware Salient Object Detection via Knowledge Transfer
https://github.com/Jittor/JDet
공식 코드https://github.com/JoeRoussy/adaptive-attention-in-cv
공식 코드https://github.com/Johann-Huber/qd_grasp
공식 코드Toward a Plug-and-Play Vision-Based Grasping Module for Robotics
https://github.com/Johnathan-Xie/ZSD-YOLO
공식 코드Zero-shot Object Detection Through Vision-Language Embedding Alignment
https://github.com/JosephChenHub/DPANet
공식 코드DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection
https://github.com/JosephChenHub/GCPANet
공식 코드Global Context-Aware Progressive Aggregation Network for Salient Object Detection
https://github.com/JosephKJ/OWOD
공식 코드https://github.com/JosephKJ/iOD
공식 코드https://github.com/JudasDie/SOTS
공식 코드https://github.com/Jun-Pu/UCOS-DA
공식 코드Unsupervised Camouflaged Object Segmentation as Domain Adaptation
https://github.com/KIT-MRT/YOLinO
공식 코드https://github.com/KPeng9510/MASS
공식 코드MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding
https://github.com/KaimingHe/resnet-1k-layers
공식 코드https://github.com/KaiyuYue/cgnl-network.pytorch
공식 코드https://github.com/KangchengLiu/FAC_Foreground_Aware_Contrast
공식 코드Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast
https://github.com/KangchengLiu/RM3D
공식 코드A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.