57 citations · 62 across the 4 of their papers we have counts for
5 papers
VST++: Efficient and Stronger Visual Saliency Transformer
Nian Liu, Ziyang Luo, Ni Zhang +1
While previous CNN-based models have exhibited promising results for salient object detection (SOD), their ability to explore global long-range dependencies is restricted. Our prev…
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Long Li, Junwei Han, Ni Zhang +5
Most previous co-salient object detection works mainly focus on extracting co-salient cues via mining the consistency relations across images while ignoring explicit exploration of…
Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
Ni Zhang, Junwei Han, Nian Liu +1
Humans perform co-saliency detection by first summarizing the consensus knowledge in the whole group and then searching corresponding objects in each image. Previous methods usuall…
Visual Saliency Transformer
Nian Liu, Ni Zhang, Kaiyuan Wan +2
Existing state-of-the-art saliency detection methods heavily rely on CNN-based architectures. Alternatively, we rethink this task from a convolution-free sequence-to-sequence persp…
Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection
Nian Liu, Ni Zhang, Ling Shao +1
How to effectively fuse cross-modal information is the key problem for RGB-D salient object detection. Early fusion and the result fusion schemes fuse RGB and depth information at…