27 citations · 41 across the 7 of their papers we have counts for
7 papers
Unsupervised Camouflaged Object Segmentation as Domain Adaptation
Yi Zhang, Chengyi Wu
Deep learning for unsupervised image segmentation remains challenging due to the absence of human labels. The common idea is to train a segmentation head, with the supervision of p…
ASOD60K: An Audio-Induced Salient Object Detection Dataset for Panoramic Videos
Yi Zhang
Exploring to what humans pay attention in dynamic panoramic scenes is useful for many fundamental applications, including augmented reality (AR) in retail, AR-powered recruitment,…
Salient Object Ranking with Position-Preserved Attention
Hao Fang, Daoxin Zhang, Yi Zhang +5
Instance segmentation can detect where the objects are in an image, but hard to understand the relationship between them. We pay attention to a typical relationship, relative salie…
SHD360: A Benchmark Dataset for Salient Human Detection in 360° Videos
Yi Zhang, Lu Zhang, Kang Wang +2
Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augment…
CMA-Net: A Cascaded Mutual Attention Network for Light Field Salient Object Detection
Yi Zhang, Lu Zhang, Wassim Hamidouche +1
In the past few years, numerous deep learning methods have been proposed to address the task of segmenting salient objects from RGB images. However, these approaches depending on s…
RESA: Recurrent Feature-Shift Aggregator for Lane Detection
Tu Zheng, Hao Fang, Yi Zhang +4
Lane detection is one of the most important tasks in self-driving. Due to various complex scenarios (e.g., severe occlusion, ambiguous lanes, etc.) and the sparse supervisory signa…
A Fixation-based 360° Benchmark Dataset for Salient Object Detection
Yi Zhang, Lu Zhang, Wassim Hamidouche +1
Fixation prediction (FP) in panoramic contents has been widely investigated along with the booming trend of virtual reality (VR) applications. However, another issue within the fie…