Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
End-to-End Video Instance Segmentation with Transformers
2021433 citationsYuqing Wang, Zhaoliang Xu et al.profile →
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
2021406 citationsXinlong Wang, Rufeng Zhang et al.profile →
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
2023239 citationsQuan Sun, Xinggang Wang et al.profile →
BoxInst: High-Performance Instance Segmentation with Box Annotations
2021200 citationsChunhua Shen, Xinlong Wang et al.profile →
SegGPT: Towards Segmenting Everything In Context
2023126 citationsXinlong Wang, Xiaosong Zhang et al.profile →
EVA-02: A visual representation for neon genesis
202462 citationsY.K. Fang, Quan Sun et al.Image and Vision Computingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Xinlong 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 Xinlong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinlong Wang more than expected).
This network shows the impact of papers produced by Xinlong 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 Xinlong Wang. The network helps show where Xinlong Wang may publish in the future.
Co-authorship network of co-authors of Xinlong Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Xinlong Wang.
A scholar is included among the top collaborators of Xinlong 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 Xinlong Wang. Xinlong Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wang, Xinlong, Xiaosong Zhang, Yue Cao, et al.. (2023). SegGPT: Towards Segmenting Everything In Context. 1130–1140.126 indexed citations breakdown →
10.
Zhao, Yang, Xinlong Wang, Xiaohan Yu, Chunlei Liu, & Yongsheng Gao. (2022). Gait-Assisted Video Person Retrieval. IEEE Transactions on Circuits and Systems for Video Technology. 33(2). 897–908.7 indexed citations
11.
Wang, Yuqing, Zhaoliang Xu, Xinlong Wang, et al.. (2021). End-to-End Video Instance Segmentation with Transformers. 8737–8746.433 indexed citations breakdown →
12.
Wang, Xinlong, Rufeng Zhang, Tao Kong, Lei Li, & Chunhua Shen. (2020). SOLOv2: Dynamic and Fast Instance Segmentation. Neural Information Processing Systems. 33. 17721–17732.25 indexed citations
13.
Wang, Xinlong, Rufeng Zhang, Tao Kong, Lei Li, & Chunhua Shen. (2020). SOLOv2: Dynamic, Faster and Stronger.. arXiv (Cornell University).56 indexed citations
Wang, Xinlong, et al.. (2012). Error modeling and analysis for random drift of MEMS gyroscopes. Beijing Hangkong Hangtian Daxue xuebao. 170.5 indexed citations
18.
Wang, Xinlong. (2006). Interface Analyse on Java Language and C language.
19.
Wang, Xinlong. (2006). Research on a fuzzy adaptive state estimator for INS/GPS integrated navigation system. Journal of Communications.6 indexed citations
20.
Wang, Xinlong. (2006). Quantificational Analysis the Observability and the Best Observable Son-Space of Inertial Navigation System. Journal of Astronautics.2 indexed citations
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.