Jianyi Wang

1.5k citations
25 papers · 663 indexed · 2 hit papers · h-index 9
Topics
Advanced Image Processing Techniques (5 papers)Image and Signal Denoising Methods (4 papers)Visual Attention and Saliency Detection (4 papers)

In The Last Decade

Jianyi Wang

22 papers receiving 652 citations

Hit Papers

Exploring CLIP for Assessing the Look and Feel of Images20232026202420252023202450100150200

Peers

Jianyi Wang
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 496
  • Media Technology 142
  • Signal Processing 77
  • Artificial Intelligence 64
  • Human-Computer Interaction 29
Replace Junru Wu with:
Junru Wu United States
Jari Korhonen Denmark
Abdolah Chalechale Iran
T.E. Boult United States
Tarik Arici United States
Xuekai Wei China
Ben Daubney United Kingdom
Hefei Ling China
Zhengzhong Tu United States
Jianyi Wang relative to Junru Wu United States Junru Wu's profile →
Citations per field
00.5×
Junru Wu · 1×
Citations per year

Countries citing papers authored by Jianyi Wang

Since Specialization
Citations

This map shows the geographic impact of Jianyi Wang'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 Jianyi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianyi Wang more than expected).

Fields of papers citing papers by Jianyi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jianyi Wang. 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 Jianyi Wang. The network helps show where Jianyi Wang may publish in the future.

Co-authorship network of co-authors of Jianyi Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jianyi Wang. A scholar is included among the top collaborators of Jianyi Wang 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 Jianyi Wang. Jianyi Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 21
3 0
4 14
5
Exploiting Diffusion Prior for Real-World Image Super-Resolutionbreakdown →
130
6 13
7 3
8
Exploring CLIP for Assessing the Look and Feel of Imagesbreakdown →
222
9 1
10 2
11 7
12 10
13 0
14 10
15 179
16
Modeling Attention in Panoramic Video: A Deep Reinforcement Learning Approach.
3
17 2
18 5
19 7
20 1

About Jianyi Wang

Jianyi Wang is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Management Information Systems, having authored 25 papers that have together received 663 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (5 papers), Image and Signal Denoising Methods (4 papers) and Visual Attention and Saliency Detection (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (496 citations), Media Technology (142 citations) and Signal Processing (77 citations). Jianyi Wang has collaborated with scholars based in China, Singapore and United Kingdom. Frequent co-authors include Chen Change Loy, Kelvin C. K. Chan, Mai Xu, Yuhang Song, Zongsheng Yue, Liangyu Huo, Zulin Wang, Minglang Qiao, Shangchen Zhou and Zhenghua Xu. Their work appears in journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision.

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.

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