标签 - Object Detection

2020
Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Meta-RCNN: Meta learning for few-shot object detection
Bounding Box Regression with Uncertainty for Accurate Object Detection
LSTD: A low-shot transfer detector for object detection
Meta-Learning to Detect Rare Objects
Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector
RepMet: Representative-based metric learning for classification and few-shot object detection
Meta R-CNN : Towards General Solver for Instance-level Low-shot Learning
Incremental Few-Shot Object Detection
Objects as Points
Few-shot Object Detection via Feature Reweighting
Few-shot Adaptive Faster R-CNN
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
Object as Distribution
FCOS: Fully Convolutional One-Stage Object Detection
Focal Loss for Dense Object Detection
2019
High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection
Learning non-maximum suppression
Improving Object Detection With One Line of Code
Seeing Small Faces from Robust Anchor’s Perspective
Deep Regionlets for Object Detection
Regionlets for Generic Object Detection
Spatial Transformer Networks
Object Detection based on Region Decomposition and Assembly
Region Proposal by Guided Anchoring
Grid RCNN
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
Bottom-up Object Detection by Grouping Extreme and Center Points
S3FD: Single Shot Scale-invariant Face Detector