https://github.com/BryanPlummer/phrase_detection
공식 코드Revisiting Image-Language Networks for Open-ended Phrase Detection
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BubblyYi/MMPedestron
공식 코드When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset
https://github.com/CAIC-AD/YOLOPv2
공식 코드YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception
https://github.com/CAMMA-public/ConvLSTM-Surgical-Tool-Tracker
공식 코드Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos
https://github.com/CAMMA-public/cholect50
공식 코드https://github.com/CAPTAIN-WHU/iSAID_Devkit
공식 코드iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
https://github.com/CASIA-IVA-Lab/ACSL
공식 코드Adaptive Class Suppression Loss for Long-Tail Object Detection
https://github.com/CASIA-IVA-Lab/DPT
공식 코드DPT: Deformable Patch-based Transformer for Visual Recognition
https://github.com/CHENGEZ/Attacking-by-Aligning
공식 코드Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detection
https://github.com/CPFL/Autoware
공식 코드LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDAR
https://github.com/CPJKU/cyolo_score_following
공식 코드Multi-modal Conditional Bounding Box Regression for Music Score Following
https://github.com/CQU-ADHRI-Lab/MI-DETR
공식 코드MI-DETR: An Object Detection Model with Multi-time Inquiries Mechanism
https://github.com/CQUlearningsystemgroup/YicongPeng
공식 코드MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
https://github.com/CSIPlab/context-aware-attacks
공식 코드https://github.com/CSL-KU/firesim-nvdla
공식 코드Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim
https://github.com/CV-IP/SADC
공식 코드https://github.com/CVMI-Lab/ST3D
공식 코드ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection
https://github.com/CVMI-Lab/SlotCon
공식 코드Self-Supervised Visual Representation Learning with Semantic Grouping
https://github.com/CXH-Research/DocShadow-SD7K
공식 코드https://github.com/CXH-Research/ShadocNet
공식 코드ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
https://github.com/CalcuLuUus/RASM
공식 코드https://github.com/Caoang327/vis_det
공식 코드https://github.com/Caojunxu/AC-FPN
공식 코드Attention-guided Context Feature Pyramid Network for Object Detection
https://github.com/CarloSgaravatti/HybridLateCascadeFusion
공식 코드A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection
https://github.com/Cc-Hy/CMKD
공식 코드Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection
https://github.com/Championchess/Tri-Layer_Plugin_Occluded_Detection
공식 코드https://github.com/ChanningPing/VideoHighlightDetection
공식 코드https://github.com/ChaofWang/AWSRN
공식 코드Lightweight Image Super-Resolution with Adaptive Weighted Learning Network
https://github.com/Chasel-Tsui/mmdet-aitod
공식 코드Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark
https://github.com/Cheeun/AdaBM
공식 코드AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution
https://github.com/Cheeun/DAQ-pytorch
공식 코드DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks
https://github.com/ChenJoya/dropit
공식 코드DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training
https://github.com/Chenglin-Yang/LESA
공식 코드Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context Terms
https://github.com/Chengxiao-Luo/Untargeted-Backdoor-Attack-against-Object-Detection
공식 코드https://github.com/ChenhongyiYang/QueryDet-PyTorch
공식 코드QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection
https://github.com/ChenhongyiYang/SG-NMS
공식 코드Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.