https://github.com/public-bots/tigdistill-bev
공식 코드TiGDistill-BEV: Multi-view BEV 3D Object Detection via Target Inner-Geometry Learning Distillation
Papers with Code 아카이브
2D Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://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/pupil-labs/pupil
공식 코드Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction
https://github.com/purduedigitaltwin/redformer
공식 코드https://github.com/putshua/inference-scale-ann-snn
공식 코드Inference-Scale Complexity in ANN-SNN Conversion for High-Performance and Low-Power Applications
https://github.com/pxiangwu/MotionNet
공식 코드https://github.com/pyun-ram/FL3D
공식 코드https://github.com/pzzhang/VinVL
공식 코드VinVL: Revisiting Visual Representations in Vision-Language Models
https://github.com/q-viper/contour-based-writing
공식 코드An Approach for Air Drawing Using Background Subtraction and Contour Extraction
https://github.com/qalam001/attentiondeficit
공식 코드https://github.com/qcraftai/cross-modal-ssl
공식 코드Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point Clouds
https://github.com/qcraftai/distill-bev
공식 코드DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation
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/qduOliver/MQP
공식 코드A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception
https://github.com/qhfan/CloFormer
공식 코드Rethinking Local Perception in Lightweight Vision Transformer
https://github.com/qhfan/RMT
공식 코드https://github.com/qianyu-dlut/mvanet
공식 코드Multi-view Aggregation Network for Dichotomous Image Segmentation
https://github.com/qianyuzqy/TransVOD_Lite
공식 코드TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers
https://github.com/qigongsun/BMD
공식 코드Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration
https://github.com/qingshufan/GeneA-SLAM2
공식 코드https://github.com/qingyonghu/viso
공식 코드Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
https://github.com/qinhongda8/ldds
공식 코드Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection
https://github.com/qinzheng93/thundernet
공식 코드https://github.com/qiujiaming315/edgeml-object-detection
공식 코드https://github.com/qjadud1994/TricubeNet
공식 코드TricubeNet: 2D Kernel-Based Object Representation for Weakly-Occluded Oriented Object Detection
https://github.com/qq456cvb/CanonicalVoting
공식 코드Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
https://github.com/qtacierp/prior
공식 코드PRIOR: Prototype Representation Joint Learning from Medical Images and Reports
https://github.com/quan-dao/apro3d-net
공식 코드Attention-based Proposals Refinement for 3D Object Detection
https://github.com/quan-dao/pc-corrector
공식 코드Aligning Bird-Eye View Representation of Point Cloud Sequences using Scene Flow
https://github.com/quan-dao/practical-collab-perception
공식 코드Practical Collaborative Perception: A Framework for Asynchronous and Multi-Agent 3D Object Detection
https://github.com/quangle2110/GAN_Mask-RCNN
공식 코드Instance Semantic Segmentation Benefits from Generative Adversarial Networks
https://github.com/quickhdsdc/Point-Tracking-for-Displacement-Measurement-in-Railway-Applications
공식 코드https://github.com/qujx/ddnet
공식 코드https://github.com/quotation2520/pg-rcnn
공식 코드PG-RCNN: Semantic Surface Point Generation for 3D Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.