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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/xiaofeng94/vl-plm
공식 코드Exploiting Unlabeled Data with Vision and Language Models for Object Detection
https://github.com/xiaohaoChen/rrc_detection
공식 코드Accurate Single Stage Detector Using Recurrent Rolling Convolution
https://github.com/xiaohulugo/ScAR-Scaling-Adversarial-Robustness-for-LiDAR-Object-Detection
공식 코드ScAR: Scaling Adversarial Robustness for LiDAR Object Detection
https://github.com/xiaohulugo/scar-iros2023
공식 코드ScAR: Scaling Adversarial Robustness for LiDAR Object Detection
https://github.com/xiaohulugo/t-ro2024-dali
공식 코드https://github.com/xiaolisean/cognitive-map
공식 코드SeanNet: Semantic Understanding Network for Localization Under Object Dynamics
https://github.com/xiaolonw/adversarial-frcnn
공식 코드A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection
https://github.com/xiaomabufei/dowb
공식 코드https://github.com/xiaomabufei/fgahoi
공식 코드FGAHOI: Fine-Grained Anchors for Human-Object Interaction Detection
https://github.com/xiaomabufei/skdf
공식 코드https://github.com/xiaomengyc/I2C
공식 코드Inter-Image Communication for Weakly Supervised Localization
https://github.com/xiaomengyc/SEM
공식 코드Rethinking Localization Map: Towards Accurate Object Perception with Self-Enhancement Maps
https://github.com/xiaomengyc/SPG
공식 코드Self-produced Guidance for Weakly-supervised Object Localization
https://github.com/xiaoqi-zhao-dlut/multi-source-aps-zvos
공식 코드Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation
https://github.com/xiaoqi-zhao-dlut/sslsod
공식 코드Self-Supervised Pretraining for RGB-D Salient Object Detection
https://github.com/xieenze/DetCo
공식 코드DetCo: Unsupervised Contrastive Learning for Object Detection
https://github.com/xieenze/Trans2Seg
공식 코드https://github.com/xiemk/mlc-pat
공식 코드Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
https://github.com/xiexh20/CHORE
공식 코드CHORE: Contact, Human and Object REconstruction from a single RGB image
https://github.com/xiexh20/behave-dataset
공식 코드BEHAVE: Dataset and Method for Tracking Human Object Interactions
https://github.com/xifen523/cod
공식 코드Towards Consistent Object Detection via LiDAR-Camera Synergy
https://github.com/xifen523/omnitrack
공식 코드https://github.com/xilin1991/CluterNet
공식 코드Online Unsupervised Video Object Segmentation via Contrastive Motion Clustering
https://github.com/xin-ran-w/controllableobjectdescription
공식 코드https://github.com/xing0047/cca-llava
공식 코드Mitigating Object Hallucination via Concentric Causal Attention
https://github.com/xingaoli/dp-hoi
공식 코드Disentangled Pre-training for Human-Object Interaction Detection
https://github.com/xinghaochen/DECO
공식 코드https://github.com/xingyizhou/CenterNet
공식 코드https://github.com/xingyizhou/ExtremeNet
공식 코드Bottom-up Object Detection by Grouping Extreme and Center Points
https://github.com/xingyizhou/GTR
공식 코드https://github.com/xingyu-group/3d-density-resampling-sdg
공식 코드Domain Generalization of 3D Object Detection by Density-Resampling
https://github.com/xinshuoweng/GNN3DMOT
공식 코드GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning
https://github.com/xinshuoweng/mono3D_PLiDAR
공식 코드https://github.com/xinw1012/cycle-confusion
공식 코드Robust Object Detection via Instance-Level Temporal Cycle Confusion
https://github.com/xinyu1205/idea-pytorch
공식 코드IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.