https://github.com/hkust-drive-ai-lab/follownet
공식 코드FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and Transformer
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and Transformer
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and Transformer
Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training
Weakly Supervised 3D Object Detection from Lidar Point Cloud
Inner and Inter Label Propagation: Salient Object Detection in the Wild
Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection
CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise Transformer
Rethinking IoU-based Optimization for Single-stage 3D Object Detection
Automatic Wood Pith Detector: Local Orientation Estimation and Robust Accumulation
Pixelwise Instance Segmentation with a Dynamically Instantiated Network
EVD4UAV: An Altitude-Sensitive Benchmark to Evade Vehicle Detection in UAV
Human-Guided Image Generation for Expanding Small-Scale Training Image Datasets
BPJDet: Extended Object Representation for Generic Body-Part Joint Detection
DirectMHP: Direct 2D Multi-Person Head Pose Estimation with Full-range Angles
Joint Multi-Person Body Detection and Orientation Estimation via One Unified Embedding
SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection
EnSolver: Uncertainty-Aware Ensemble CAPTCHA Solvers with Theoretical Guarantees
A DeNoising FPN With Transformer R-CNN for Tiny Object Detection
MonoTAKD: Teaching Assistant Knowledge Distillation for Monocular 3D Object Detection
The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images
Aligning Pretraining for Detection via Object-Level Contrastive Learning
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.