Papers with Code 아카이브
Object
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
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/AlamiMejjati/GeneratingObjectStamps
공식 코드https://github.com/AlbertSuarez/object-cut
공식 코드Boundary-Aware Segmentation Network for Mobile and Web Applications
https://github.com/AlejandroBarrera/birdnet2
공식 코드BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View
https://github.com/AlexeyAB/darknet
공식 코드https://github.com/Ali2500/HODOR
공식 코드HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images
https://github.com/AliaksandrSiarohin/first-order-model
공식 코드https://github.com/AliaksandrSiarohin/monkey-net
공식 코드https://github.com/AlibabaResearch/efficientteacher
공식 코드Efficient Teacher: Semi-Supervised Object Detection for YOLOv5
https://github.com/AljazBozic/NeuralGraph
공식 코드Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction
https://github.com/AlmoonYsl/OPEN
공식 코드OPEN: Object-wise Position Embedding for Multi-view 3D Object Detection
https://github.com/AlonZolfi/YolOOD
공식 코드YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection
https://github.com/Alvinosaur/opa
공식 코드Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method
https://github.com/AnasIbrahim/image_agnostic_segmentation
공식 코드DoUnseen: Tuning-Free Class-Adaptive Object Detection of Unseen Objects for Robotic Grasping
https://github.com/AndreaHor/LifT_Solver
공식 코드Lifted Disjoint Paths with Application in Multiple Object Tracking
https://github.com/AngeloFang/MIPR_UAAN
공식 코드Uncertainty-Guided Appearance-Motion Association Network for Out-of-Distribution Action Detection
https://github.com/ArashNasrEsfahani/Object-Rearrangement-in-Dynamic-Environments
공식 코드AI-Driven Relocation Tracking in Dynamic Kitchen Environments
https://github.com/ArminLee/OWOD_Review
공식 코드https://github.com/AutoAILab/DynamicDepth
공식 코드Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth
https://github.com/AutoCompSysLab/DCTNet
공식 코드https://github.com/AutoVision-cloud/Deformable-PV-RCNN
공식 코드Deformable PV-RCNN: Improving 3D Object Detection with Learned Deformations
https://github.com/AutoVision-cloud/SA-Det3D
공식 코드SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection
https://github.com/Ayush8120/COAT
공식 코드Physical Reasoning and Object Planning for Household Embodied Agents
https://github.com/BCV-Uniandes/query-objseg
공식 코드Dynamic Multimodal Instance Segmentation guided by natural language queries
https://github.com/BICLab/EMS-YOLO
공식 코드Deep Directly-Trained Spiking Neural Networks for Object Detection
https://github.com/BIT-DYN/OpenObj
공식 코드OpenObj: Open-Vocabulary Object-Level Neural Radiance Fields with Fine-Grained Understanding
https://github.com/BOBrown/JADF-caffe
공식 코드Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection
https://github.com/Bahram-Mohammadi/ACK
공식 코드https://github.com/Bartzi/loans
공식 코드LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks
https://github.com/BathVisArtData/PeopleArt
공식 코드https://github.com/Benzlxs/tDBN
공식 코드Three-dimensional Backbone Network for 3D Object Detection in Traffic Scenes
https://github.com/BestAnHongjun/GILM
공식 코드https://github.com/BichenWuUCB/squeezeDet
공식 코드https://github.com/BingfengYan/DS_OCSORT
공식 코드Multiple Object Tracking Challenge Technical Report for Team MT_IoT
https://github.com/Bissmella/Small-object-detection-transformers
공식 코드Multimodal Transformer Using Cross-Channel attention for Object Detection in Remote Sensing Images
https://github.com/BoPang1996/TubeTK
공식 코드TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.