https://github.com/Boshrakh/Yolov8-Small-Object-Detection-Arial-Images
공식 코드SOD-YOLOv8 -- Enhancing YOLOv8 for Small Object Detection in Traffic Scenes
Papers with Code 아카이브
2D Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BoulderDS/LARN
공식 코드No Permanent Friends or Enemies: Tracking Relationships between Nations from News
https://github.com/Breakend/TemporalYolo
공식 코드Underwater Multi-Robot Convoying using Visual Tracking by Detection
https://github.com/BrunoSauvalle/AST
공식 코드Unsupervised Multi-object Segmentation Using Attention and Soft-argmax
https://github.com/BryanPlummer/phrase_detection
공식 코드Revisiting Image-Language Networks for Open-ended Phrase Detection
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/CAMERA-MRI/SPARK2023/tree/main/SPARK_BTS_KIFARU
공식 코드https://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/CCCjiang/CTRL
공식 코드An Embarrassingly Simple Backdoor Attack on Self-supervised Learning
https://github.com/CHENGEZ/Attacking-by-Aligning
공식 코드Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detection
https://github.com/CHUNYUWANG/imu-human-pose-pytorch
공식 코드Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach
https://github.com/CMU-Perceptual-Computing-Lab/openpose
공식 코드OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
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/CQFIO/FastImageProcessing
공식 코드https://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/CVMI-Lab/HybridNeuralRendering
공식 코드Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
https://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/FilmNet
공식 코드A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
https://github.com/CZFuChason/SeMemNN
공식 코드SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification
https://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/ChaofanTao/FAT_Quantization
공식 코드FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation
https://github.com/Chasel-Tsui/mmdet-aitod
공식 코드Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.