148 citations · 197 across the 10 of their papers we have counts for
11 papers
Robust Object Detection of Underwater Robot based on Domain Generalization
Pinhao Song
Object detection aims to obtain the location and the category of specific objects in a given image, which includes two tasks: classification and location. In recent years, research…
Domain Similarity-Perceived Label Assignment for Domain Generalized Underwater Object Detection
Xisheng Li, Wei Li, Pinhao Song +2
The inherent characteristics and light fluctuations of water bodies give rise to the huge difference between different layers and regions in underwater environments. When the test…
A Gated Cross-domain Collaborative Network for Underwater Object Detection
Linhui Dai, Hong Liu, Pinhao Song +1
Underwater object detection (UOD) plays a significant role in aquaculture and marine environmental protection. Considering the challenges posed by low contrast and low-light condit…
Edge-guided Representation Learning for Underwater Object Detection
Linhui Dai, Hong Liu, Pinhao Song +3
Underwater object detection (UOD) is crucial for marine economic development, environmental protection, and the planet's sustainable development. The main challenges of this task a…
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action Recognition
Zhan Chen, Hong Liu, Tianyu Guo +3
Self-supervised skeleton-based action recognition with contrastive learning has attracted much attention. Recent literature shows that data augmentation and large sets of contrasti…
Excavating RoI Attention for Underwater Object Detection
Xutao Liang, Pinhao Song
Self-attention is one of the most successful designs in deep learning, which calculates the similarity of different tokens and reconstructs the feature based on the attention matri…
Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detection
Pinhao Song, Pengteng Li, Linhui Dai +2
Complicated underwater environments bring new challenges to object detection, such as unbalanced light conditions, low contrast, occlusion, and mimicry of aquatic organisms. Under…
AO2-DETR: Arbitrary-Oriented Object Detection Transformer
Linhui Dai, Hong Liu, Hao Tang +2
Arbitrary-oriented object detection (AOOD) is a challenging task to detect objects in the wild with arbitrary orientations and cluttered arrangements. Existing approaches are mainl…
Pose-guided Feature Disentangling for Occluded Person Re-identification Based on Transformer
Tao Wang, Hong Liu, Pinhao Song +2
Occluded person re-identification is a challenging task as human body parts could be occluded by some obstacles (e.g. trees, cars, and pedestrians) in certain scenes. Some existing…
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning
Yang Chen, Pinhao Song, Hong Liu +4
The performance of existing underwater object detection methods degrades seriously when facing domain shift caused by complicated underwater environments. Due to the limitation of…
WQT and DG-YOLO: towards domain generalization in underwater object detection
Hong Liu, Pinhao Song, Runwei Ding
A General Underwater Object Detector (GUOD) should perform well on most of underwater circumstances. However, with limited underwater dataset, conventional object detection methods…