2D Object Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ztt1024/densessl
공식 코드De-coupling and De-positioning Dense Self-supervised Learning
https://github.com/ztx-100/dla-combined-ious
공식 코드Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs
https://github.com/ztx-100/efficient_vit_with_dw
공식 코드Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets
https://github.com/zubair-irshad/NeRF-MAE
공식 코드https://github.com/zubair-irshad/shapo
공식 코드ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization
https://github.com/zwbx/BTS-Net
공식 코드BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection
https://github.com/zwbx/DFM-Net
공식 코드Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection
https://github.com/zxcvfd13502/ddas_code
공식 코드https://github.com/zyfone/dpa
공식 코드Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment
https://github.com/zyjwuyan/BBS-Net
공식 코드Bifurcated backbone strategy for RGB-D salient object detection
https://github.com/zyn-1101/dandr
공식 코드https://github.com/zyrant/cpdet3d
공식 코드Learning Class Prototypes for Unified Sparse Supervised 3D Object Detection
https://github.com/zyrant/spgroup3d
공식 코드SPGroup3D: Superpoint Grouping Network for Indoor 3D Object Detection
https://github.com/zyszxhy/fora
공식 코드FoRA: Low-Rank Adaptation Model beyond Multimodal Siamese Network
https://github.com/zyw-stu/CPA-Enhancer
공식 코드https://github.com/zyyyyy0926/pointcformer_plus_pytorch
공식 코드PointCFormer: a Relation-based Progressive Feature Extraction Network for Point Cloud Completion
https://github.com/zzh-tju/zoneeval
공식 코드https://github.com/zzj403/BEV_Robust
공식 코드https://github.com/zzy-zhou/renet
공식 코드RGB-Event Fusion for Moving Object Detection in Autonomous Driving
https://github.com/zzy816/com
공식 코드Curricular Object Manipulation in LiDAR-based Object Detection
https://github.com/zzy816/corp
공식 코드Co-Salient Object Detection with Co-Representation Purification
https://gitlab.au.dk/maleci/opendr/ua-ab3dmot
공식 코드Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
https://gitlab.au.dk/maleci/opendr/variational-voxel-3d-detetction
공식 코드Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
https://gitlab.com/Avya/deepher2
공식 코드https://gitlab.com/CBDS/DeepSolaris
공식 코드https://gitlab.com/EAVISE/jetnet
공식 코드Super accurate low latency object detection on a surveillance UAV
https://gitlab.com/Ryukijano/ESRGAN_AND_YOLOV7
공식 코드https://gitlab.com/UnBVision/edgenet
공식 코드EdgeNet: Semantic Scene Completion from a Single RGB-D Image
https://gitlab.com/etaghvaei0098/covid-19-personal-protective-equipment-detection-using-real-time-deep-learning-methods
공식 코드COVID-19 personal protective equipment detection using real-time deep learning methods
https://gitlab.com/grains2/Faster-LTN
공식 코드Faster-LTN: a neuro-symbolic, end-to-end object detection architecture
https://gitlab.com/mipl/mtl-ss
공식 코드Empirical Study of Multi-Task Hourglass Model for Semantic Segmentation Task
https://gitlab.com/sustainable-continuum-monitoring/self-adaptive-moop
공식 코드An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the Edge
https://gitlab.com/viper-purdue/lic-pruning
공식 코드Structured Pruning and Quantization for Learned Image Compression
https://gitlab.kitware.com/darpa_learn/learn
공식 코드LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning
https://huggingface.co/sparks-solutions/ELAM-7B
공식 코드Leveraging Vision-Language Models for Visual Grounding and Analysis of Automotive UI
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.