Nian Liu
- Computer Vision and Pattern Recognition top 0.2%
- Cognitive Neuroscience top 2%
- Sensory Systems top 0.5%
- Media Technology top 0.5%
- Artificial Intelligence top 2%
- Topics
- Visual Attention and Saliency Detection (34 papers)Advanced Image and Video Retrieval Techniques (27 papers)Advanced Neural Network Applications (21 papers)
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Pattern Analysis and Machine IntelligenceThe Journal of Comparative Neurology
- Partner nations
- ChinaUnited Arab EmiratesUnited States
In The Last Decade
Nian Liu
79 papers receiving 4.7k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Computer Vision and Pattern Recognition 3.7k
- Cognitive Neuroscience 787
- Sensory Systems 717
- Media Technology 588
- Artificial Intelligence 483
Countries citing papers authored by Nian Liu
This map shows the geographic impact of Nian Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nian Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nian Liu more than expected).
Fields of papers citing papers by Nian Liu
This network shows the impact of papers produced by Nian Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nian Liu. The network helps show where Nian Liu may publish in the future.
Co-authorship network of co-authors of Nian Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Nian Liu. A scholar is included among the top collaborators of Nian Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nian Liu. Nian Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 9 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 5 | |
| 9 | 12 | |
| 10 | 49 | |
| 11 | 38 | |
| 12 | 13 | |
| 13 | 28 | |
| 14 | Harmonizing Performance and Isolation in Microkernels with Efficient Intra-kernel Isolation and Communication | 10 |
| 15 | CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusionbreakdown → | 337 |
| 16 | PiCANet: Learning Pixel-wise Contextual Attention in ConvNets and Its Application in Saliency Detection. | 2 |
| 17 | 79 | |
| 18 | Sub-Pixel object-Image Registration Using Improved Iterative Closest Point Method | 1 |
| 19 | Application of Risk Management in the Hydropower Engineering Construction | 0 |
| 20 | 2 |
About Nian Liu
Nian Liu is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems and Human-Computer Interaction, having authored 83 papers that have together received 4.8k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (34 papers), Advanced Image and Video Retrieval Techniques (27 papers) and Advanced Neural Network Applications (21 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.7k citations), Sensory Systems (717 citations) and Media Technology (588 citations). Nian Liu has collaborated with scholars based in China, United Arab Emirates and United States. Frequent co-authors include Junwei Han, Ming–Hsuan Yang, Dingwen Zhang, Ni Zhang, Dong Xu, Ling Shao, Gong Cheng, Xuelong Li, Hao Chen and Chenggang Yan. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Journal of Comparative Neurology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.