https://github.com/xinyusun/psl-instancenav
공식 코드Prioritized Semantic Learning for Zero-shot Instance Navigation
Papers with Code 아카이브
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xinzhuma/monodle
공식 코드Delving into Localization Errors for Monocular 3D Object Detection
https://github.com/xjtu-haolin/point_assisted_sample_selection
공식 코드Leveraging Anchor-based LiDAR 3D Object Detection via Point Assisted Sample Selection
https://github.com/xl-sr/THOR
공식 코드https://github.com/xmuqimingxia/dota
공식 코드Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual Labels
https://github.com/xternalz/AE-WTN
공식 코드Scaling Object Detection by Transferring Classification Weights
https://github.com/xud-yan/Trident
공식 코드Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot Learning
https://github.com/xukechun/gsp
공식 코드Grasp, See, and Place: Efficient Unknown Object Rearrangement with Policy Structure Prior
https://github.com/xulianuwa/mctformer
공식 코드Multi-class Token Transformer for Weakly Supervised Semantic Segmentation
https://github.com/xuqingyu26/hgtmt
공식 코드Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos
https://github.com/xushilin1/dst-det
공식 코드DST-Det: Simple Dynamic Self-Training for Open-Vocabulary Object Detection
https://github.com/xuxw98/backtoreality
공식 코드Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement
https://github.com/xuxw98/dspdet3d
공식 코드https://github.com/xvjiarui/VFS
공식 코드Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/xwinks/llm_articulated_object_manipulation
공식 코드Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs
https://github.com/y2863/MetaGraspNet
공식 코드https://github.com/yael-vinker/CLIPasso
공식 코드https://github.com/yahoo/object_relation_transformer
공식 코드https://github.com/yahoo/photo-background-generation
공식 코드Salient Object-Aware Background Generation using Text-Guided Diffusion Models
https://github.com/yancie-yjr/StreamYOLO
공식 코드https://github.com/yang-yk/NP-RepMet
공식 코드https://github.com/yangcao1996/fanet
공식 코드https://github.com/yangcaoai/CoDA_NeurIPS2023
공식 코드https://github.com/yangfan293/gaaf-dex
공식 코드https://github.com/yanghai-1218/radet
공식 코드https://github.com/yanghai-1218/scflow
공식 코드Shape-Constraint Recurrent Flow for 6D Object Pose Estimation
https://github.com/yanglei18/Lite-FPN
공식 코드https://github.com/yangli18/pdnet
공식 코드PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling
https://github.com/yangxh11/p2p-net
공식 코드Fine-Grained Object Classification via Self-Supervised Pose Alignment
https://github.com/yangxue0827/RotationDetection
공식 코드RSDet++: Point-based Modulated Loss for More Accurate Rotated Object Detection
https://github.com/yangxue0827/STAR-MMRotate
공식 코드https://github.com/yangxue0827/h2rbox-jittor
공식 코드H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection
https://github.com/yangxue0827/h2rbox-mmrotate
공식 코드H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection
https://github.com/yangxue0827/rsg-mmrotate
공식 코드https://github.com/yangxuntu/vrd
공식 코드Shuffle-Then-Assemble: Learning Object-Agnostic Visual Relationship Features
https://github.com/yanhaowu/oessl
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.