https://github.com/saltoricristiano/SF-UDA-3DV
공식 코드SF-UDA$^{3D}$: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection
Papers with Code 아카이브
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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/samaonline/Trajectory-Regularization-Enhances-Self-Supervised-Geometric-Representation
공식 코드Pose-Aware Self-Supervised Learning with Viewpoint Trajectory Regularization
https://github.com/samarth-robo/ContactPose-ML
공식 코드ContactPose: A Dataset of Grasps with Object Contact and Hand Pose
https://github.com/samarth-robo/contactdb_prediction
공식 코드ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
https://github.com/samarth-robo/contactdb_utils
공식 코드ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
https://github.com/samarth-robo/py-faster-rcnn
공식 코드https://github.com/samiksome/faster-rcnn.pytorch
공식 코드https://github.com/samwilso/safe_official
공식 코드SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection
https://github.com/sanghoon/pva-faster-rcnn
공식 코드PVANet: Lightweight Deep Neural Networks for Real-time Object Detection
https://github.com/sangminwoo/Local-to-Global-Interaction-Networks-SGG
공식 코드Tackling the Challenges in Scene Graph Generation with Local-to-Global Interactions
https://github.com/sangminwoo/svol
공식 코드https://github.com/sanket0707/bimodal-segnet
공식 코드Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Grasping
https://github.com/sanketsans/ganov2
공식 코드Enhancing Next Active Object-based Egocentric Action Anticipation with Guided Attention
https://github.com/sanmin0312/P2D
공식 코드Predict to Detect: Prediction-guided 3D Object Detection using Sequential Images
https://github.com/sarkar-rohan/objectswithstatechange
공식 코드A Dataset and Framework for Learning State-invariant Object Representations
https://github.com/sashamatsun/lskdiffdet
공식 코드Innovative Horizons in Aerial Imagery: LSKNet Meets DiffusionDet for Advanced Object Detection
https://github.com/satish1901/LOCL-Learning-Object-Attribute-Composition-using-Localization
공식 코드LOCL: Learning Object-Attribute Composition using Localization
https://github.com/saurav-31/vitol
공식 코드ViTOL: Vision Transformer for Weakly Supervised Object Localization
https://github.com/say2l/dcdet
공식 코드https://github.com/say2l/ffam
공식 코드FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors
https://github.com/sayantan11995/affordance
공식 코드TEXT2AFFORD: Probing Object Affordance Prediction abilities of Language Models solely from Text
https://github.com/sbasu276/Weakly_DETR
공식 코드Gall Bladder Cancer Detection from US Images with Only Image Level Labels
https://github.com/sbelharbi/colo-cam
공식 코드CoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videos
https://github.com/sbelharbi/tcam-wsol-video
공식 코드TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos
https://github.com/sberbank-ai/DetIE
공식 코드DetIE: Multilingual Open Information Extraction Inspired by Object Detection
https://github.com/scaelles/DEXTR-KerasTensorflow
공식 코드Deep Extreme Cut: From Extreme Points to Object Segmentation
https://github.com/scaelles/DEXTR-PyTorch
공식 코드Deep Extreme Cut: From Extreme Points to Object Segmentation
https://github.com/scale-lab/AdaCon
공식 코드AdaCon: Adaptive Context-Aware Object Detection for Resource-Constrained Embedded Devices
https://github.com/scheckmedia/centernet-uda
공식 코드Unsupervised Domain Adaptation from Synthetic to Real Images for Anchorless Object Detection
https://github.com/sciencefans/RSA-for-object-detection
공식 코드https://github.com/scnu-rislab/cv-mos
공식 코드https://github.com/scnu-rislab/mf-mos
공식 코드MF-MOS: A Motion-Focused Model for Moving Object Segmentation
https://github.com/scuwyh2000/randbox
공식 코드https://github.com/scy639/extreme-two-view-geometry-from-object-poses-with-diffusion-models
공식 코드Extreme Two-View Geometry From Object Poses with Diffusion Models
https://github.com/scy639/gen2sm
공식 코드Generalizable Single-view Object Pose Estimation by Two-side Generating and Matching
https://github.com/sdy1999/eamnet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.