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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/proy3/NLAP-net_VAD
공식 코드Predicting Next Local Appearance for Video Anomaly Detection
https://github.com/psc0628/dm-osvp
공식 코드Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning
https://github.com/psmmettes/object-priors-unseen-actions
공식 코드https://github.com/pter61/context-i2w
공식 코드https://github.com/ptrvilya/object-popup
공식 코드Object pop-up: Can we infer 3D objects and their poses from human interactions alone?
https://github.com/pubgeo/monocular-geocentric-pose
공식 코드https://github.com/pufanqi23/monodgp
공식 코드MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors
https://github.com/pumpkinder/glip-cdfsod
공식 코드NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results
https://github.com/pyun-ram/FL3D
공식 코드https://github.com/pzzhang/VinVL
공식 코드VinVL: Revisiting Visual Representations in Vision-Language Models
https://github.com/qa276390/searchtrack
공식 코드SearchTrack: Multiple Object Tracking with Object-Customized Search and Motion-Aware Features
https://github.com/qcraftai/pillarnext
공식 코드PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds
https://github.com/qcraftai/simtrack
공식 코드Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
https://github.com/qianyiwu/objectsdf_plus
공식 코드ObjectSDF++: Improved Object-Compositional Neural Implicit Surfaces
https://github.com/qianyiwu/objsdf
공식 코드https://github.com/qianyuzqy/TransVOD_Lite
공식 코드TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers
https://github.com/qingyonghu/viso
공식 코드Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
https://github.com/qinzheng2000/generaltrack
공식 코드https://github.com/qinzheng93/thundernet
공식 코드https://github.com/qiujiaming315/edgeml-object-detection
공식 코드https://github.com/qiuyu96/LeviTor
공식 코드https://github.com/qizekun/ShapeLLM
공식 코드ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/qjadud1994/TricubeNet
공식 코드TricubeNet: 2D Kernel-Based Object Representation for Weakly-Occluded Oriented Object Detection
https://github.com/qq456cvb/UKPGAN
공식 코드https://github.com/qq456cvb/oneloc
공식 코드https://github.com/quan-dao/apro3d-net
공식 코드Attention-based Proposals Refinement for 3D Object Detection
https://github.com/quantingxie/reasonedexplorer
공식 코드Reasoning about the Unseen for Efficient Outdoor Object Navigation
https://github.com/qxgeng/dea-net
공식 코드Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images
https://github.com/qy-feng/CRN
공식 코드https://github.com/qy1994-0919/cfpnet
공식 코드https://github.com/qyh-bit/hsod-bit-v2
공식 코드HSOD-BIT-V2: A New Challenging Benchmarkfor Hyperspectral Salient Object Detection
https://github.com/r-pad/se3_distributions
공식 코드Learning Orientation Distributions for Object Pose Estimation
https://github.com/rafa-cxg/PySGG-cxg
공식 코드LANDMARK: Language-guided Representation Enhancement Framework for Scene Graph Generation
https://github.com/rainbowluocs/diffusiontrack
공식 코드https://github.com/ramtin-ma/videosynopsis-fgs
공식 코드A Low-Computational Video Synopsis Framework with a Standard Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.