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/ckm3/Deep-Transit
공식 코드https://github.com/ckm3/deep-lc
공식 코드https://github.com/cleanlab/cleanlab
공식 코드ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data
https://github.com/clin1223/vldet
공식 코드Learning Object-Language Alignments for Open-Vocabulary Object Detection
https://github.com/clinicalml/onboarding_human_ai
공식 코드Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
https://github.com/cliu2/mtrans
공식 코드Multimodal Transformer for Automatic 3D Annotation and Object Detection
https://github.com/clobotics/piou
공식 코드PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments
https://github.com/clovaai/AdamP
공식 코드AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
https://github.com/clovaai/frostnet
공식 코드FrostNet: Towards Quantization-Aware Network Architecture Search
https://github.com/clovaai/genas
공식 코드GeNAS: Neural Architecture Search with Better Generalization
https://github.com/clovaai/overhaul-distillation
공식 코드https://github.com/clovaai/proxydet
공식 코드ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open-Vocabulary Object Detection
https://github.com/clovaai/rexnet
공식 코드https://github.com/clovaai/wsss-bed
공식 코드Rethinking Saliency-Guided Weakly-Supervised Semantic Segmentation
https://github.com/cltl/pepper
공식 코드Leolani: a reference machine with a theory of mind for social communication
https://github.com/clusterformer/clusterformer
공식 코드https://github.com/clxia12/rt-detrv3
공식 코드RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervision
https://github.com/cmb-chula/recasnet
공식 코드ReCasNet: Improving consistency within the two-stage mitosis detection framework
https://github.com/cmcin019/tm-evo
공식 코드https://github.com/cmpute/mmdetection3d
공식 코드Uncertainty-Aware Voxel based 3D Object Detection and Tracking with von-Mises Loss
https://github.com/cmsflash/efficient-attention
공식 코드https://github.com/cmu-enyac/VirtualPooling
공식 코드ViP: Virtual Pooling for Accelerating CNN-based Image Classification and Object Detection
https://github.com/cnyvfang/multicos
공식 코드Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well
https://github.com/cnyvfang/unicos
공식 코드Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well
https://github.com/cocoboom/fsd-bev
공식 코드FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object Detection
https://github.com/codereef-ai/client
공식 코드https://github.com/cogsys-tuebingen/cp_eval
공식 코드Comprehensive Analysis of the Object Detection Pipeline on UAVs
https://github.com/cogsys-tuebingen/crow_tiling
공식 코드Tackling the Background Bias in Sparse Object Detection via Cropped Windows
https://github.com/coldmanck/RVL-BERT
공식 코드Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations
https://github.com/colindecourt/record
공식 코드A recurrent CNN for online object detection on raw radar frames
https://github.com/comedialkb/learning_with_passive_optical_nonlinear_mapping
공식 코드Nonlinear optical encoding enabled by recurrent linear scattering
https://github.com/computer-vision-in-the-wild/cvinw_readings
공식 코드ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
https://github.com/conorosully/edge-detection-metrics
공식 코드The Effectiveness of Edge Detection Evaluation Metrics for Automated Coastline Detection
https://github.com/conorosully/swed-edge-detection
공식 코드Automated Coastline Extraction Using Edge Detection Algorithms
https://github.com/continental/uncertainty-detection-autolabeling
공식 코드Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.