https://github.com/naver-ai/egtr
공식 코드EGTR: Extracting Graph from Transformer for Scene Graph Generation
Papers with Code 아카이브
Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/naver-ai/pit
공식 코드https://github.com/naver-ai/rdnet
공식 코드https://github.com/naver-ai/relabel_imagenet
공식 코드Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
https://github.com/naver-ai/vidt
공식 코드ViDT: An Efficient and Effective Fully Transformer-based Object Detector
https://github.com/naver/croco
공식 코드CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
https://github.com/naver/shine
공식 코드SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object Detection
https://github.com/navervision/mlsd
공식 코드https://github.com/navervision/tsst
공식 코드Task Specific Attention is one more thing you need for object detection
https://github.com/nazmul-karim170/FIP-Fisher-Backdoor-Removal
공식 코드Fisher Information guided Purification against Backdoor Attacks
https://github.com/nazmul-karim170/NFT-Augmented-Backdoor-Purification
공식 코드Augmented Neural Fine-Tuning for Efficient Backdoor Purification
https://github.com/nblt/twa
공식 코드Trainable Weight Averaging: A General Approach for Subspace Training
https://github.com/ndrplz/semiparametric
공식 코드Warp and Learn: Novel Views Generation for Vehicles and Other Objects
https://github.com/ndwxhmzz/un-detr
공식 코드UN-DETR: Promoting Objectness Learning via Joint Supervision for Unknown Object Detection
https://github.com/neeharperi/futuredet
공식 코드https://github.com/nenadmarkus/pico
공식 코드Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/neouyghur/sess
공식 코드https://github.com/nerminsamet/houghnet
공식 코드HoughNet: Integrating near and long-range evidence for bottom-up object detection
https://github.com/nerminsamet/ppdet
공식 코드https://github.com/nesl/adversarial_audio
공식 코드Did you hear that? Adversarial Examples Against Automatic Speech Recognition
https://github.com/nesl/eagle_ptz_cameras
공식 코드Eagle: End-to-end Deep Reinforcement Learning based Autonomous Control of PTZ Cameras
https://github.com/neu-vi/diag-hoi
공식 코드https://github.com/neurai-lab/mono-pose-attack
공식 코드https://github.com/neurai-lab/mt-sfmlearner
공식 코드https://github.com/new-stone-object/DNTD
공식 코드https://github.com/newsdata/SoccerDB
공식 코드SoccerDB: A Large-Scale Database for Comprehensive Video Understanding
https://github.com/nexer8/se3d
공식 코드SE3D: A Framework For Saliency Method Evaluation In 3D Imaging
https://github.com/nexiakele/AMSODFirst
공식 코드https://github.com/nguyentthong/Paper-VLP
공식 코드https://github.com/nhcha6/classdistributionprediction
공식 코드Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection
https://github.com/nian-liu/PiCANet
공식 코드PiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection
https://github.com/nicaogr/Mi_max
공식 코드https://github.com/nicholascg/glare_dataset
공식 코드https://github.com/nicholasli1995/s-3d-rcnn
공식 코드Joint stereo 3D object detection and implicit surface reconstruction
https://github.com/nicholasli1995/snvc
공식 코드https://github.com/nickgkan/butd_detr
공식 코드Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Clouds
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.