Chih‐Yao Ma

2.0k total citations · 1 hit paper
18 papers, 898 citations indexed

About

Chih‐Yao Ma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Chih‐Yao Ma has authored 18 papers receiving a total of 898 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Media Technology. Recurrent topics in Chih‐Yao Ma's work include Multimodal Machine Learning Applications (9 papers), Advanced Neural Network Applications (7 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Chih‐Yao Ma is often cited by papers focused on Multimodal Machine Learning Applications (9 papers), Advanced Neural Network Applications (7 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Chih‐Yao Ma collaborates with scholars based in United States, Taiwan and Israel. Chih‐Yao Ma's co-authors include Zsolt Kira, Ghassan AlRegib, Yen‐Cheng Liu, Zuxuan Wu, Caiming Xiong, Min-Hung Chen, Richard Socher, Larry S. Davis, Chia-Wen Kuo and Junjiao Tian and has published in prestigious journals such as Journal of Vision, Signal Processing Image Communication and Journal of Display Technology.

In The Last Decade

Chih‐Yao Ma

17 papers receiving 868 citations

Hit Papers

align trajectories

What are hit papers?

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.

Cross-Domain Adaptive Teacher for Object Detection

2022 139 citations Yu-Jhe Li, Xiaoliang Dai et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chih‐Yao Ma United States	11	734	413	75	72	58	18	898
Rohit Girdhar United States	13	794 1.1×	388 0.9×	70 0.9×	87 1.2×	29 0.5×	19	1.2k
Antonino Furnari Italy	15	671 0.9×	252 0.6×	46 0.6×	74 1.0×	32 0.6×	61	825
Imran Saleemi United States	12	1.2k 1.6×	763 1.8×	65 0.9×	39 0.5×	43 0.7×	14	1.3k
Tao Zhao China	9	802 1.1×	353 0.9×	75 1.0×	70 1.0×	50 0.9×	13	916
Zhenjiang Miao China	13	698 1.0×	222 0.5×	64 0.9×	47 0.7×	156 2.7×	101	860
Ping Wei China	20	845 1.2×	366 0.9×	120 1.6×	61 0.8×	84 1.4×	102	1.1k
Michael D. Breitenstein Switzerland	9	1.1k 1.5×	430 1.0×	72 1.0×	181 2.5×	34 0.6×	11	1.2k
Tianshan Liu Hong Kong	16	445 0.6×	209 0.5×	95 1.3×	84 1.2×	69 1.2×	54	658
Yeon-Ho Kim South Korea	9	656 0.9×	216 0.5×	163 2.2×	37 0.5×	35 0.6×	12	783

Countries citing papers authored by Chih‐Yao Ma

Since Specialization

Citations

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

Fields of papers citing papers by Chih‐Yao Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chih‐Yao Ma. 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 Chih‐Yao Ma. The network helps show where Chih‐Yao Ma may publish in the future.

Co-authorship network of co-authors of Chih‐Yao Ma

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Wang, Hongjie, Chih‐Yao Ma, Yen‐Cheng Liu, et al.. (2025). LinGen: Towards High-Resolution Minute-Length Text-to-Video Generation with Linear Computational Complexity. 2578–2588.

Tsai, Sam S., BoRui Wu, Jialiang Wang, et al.. (2024). ControlRoom3D: Room Generation Using Semantic Proxy Rooms. 6201–6210. 5 indexed citations

Dai, Xiaoliang, et al.. (2023). Trainable Projected Gradient Method for Robust Fine-Tuning. 7836–7845. 6 indexed citations

Kuo, Chia-Wen, Chih‐Yao Ma, Judy Hoffman, & Zsolt Kira. (2023). Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 1104–1113. 3 indexed citations

Liu, Yen‐Cheng, Chih‐Yao Ma, & Zsolt Kira. (2022). Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9809–9818. 81 indexed citations

Li, Yu-Jhe, Xiaoliang Dai, Chih‐Yao Ma, et al.. (2022). Cross-Domain Adaptive Teacher for Object Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 7571–7580. 139 indexed citations breakdown →

Ma, Chih‐Yao, et al.. (2021). Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation. 13238–13246. 29 indexed citations

Liu, Yen‐Cheng, Chih‐Yao Ma, Zijian He, et al.. (2021). Unbiased Teacher for Semi-Supervised Object Detection. arXiv (Cornell University). 9 indexed citations

Liu, Yen‐Cheng, et al.. (2020). Who2com: Collaborative Perception via Learnable Handshake Communication. 6876–6883. 100 indexed citations

10.

Ma, Chih‐Yao, Jiasen Lu, Zuxuan Wu, et al.. (2019). Self-Monitoring Navigation Agent via Auxiliary Progress Estimation. arXiv (Cornell University). 26 indexed citations

11.

Ma, Chih‐Yao, Zuxuan Wu, Ghassan AlRegib, Caiming Xiong, & Zsolt Kira. (2019). The Regretful Agent: Heuristic-Aided Navigation Through Progress Estimation. 6725–6733. 98 indexed citations

12.

Wu, Zuxuan, Caiming Xiong, Chih‐Yao Ma, Richard Socher, & Larry S. Davis. (2019). AdaFrame: Adaptive Frame Selection for Fast Video Recognition. 1278–1287. 123 indexed citations

13.

Ma, Chih‐Yao, et al.. (2018). Attend and Interact: Higher-Order Object Interactions for Video Understanding. 6790–6800. 80 indexed citations

14.

Ma, Chih‐Yao, Min-Hung Chen, Zsolt Kira, & Ghassan AlRegib. (2018). TS-LSTM and temporal-inception: Exploiting spatiotemporal dynamics for activity recognition. Signal Processing Image Communication. 71. 76–87. 155 indexed citations

15.

Ma, Chih‐Yao & Hsueh‐Ming Hang. (2015). Learning-based saliency model with depth information. Journal of Vision. 15(6). 19–19. 21 indexed citations

16.

Ma, Chih‐Yao, Yung-Chia Chang, & Yi‐Pai Huang. (2014). Multi-Zone Digital Crosstalk Reduction by Image Processing in 3D Display. Journal of Display Technology. 10(6). 488–493. 6 indexed citations

17.

Ma, Chih‐Yao, et al.. (2011). 55.2: A Simulation Platform and Crosstalk Analysis for Patterned Retarder 3D Display. SID Symposium Digest of Technical Papers. 42(1). 808–811. 4 indexed citations

18.

Chang, Yu‐Cheng, Chih‐Yao Ma, & Yi‐Pai Huang. (2010). 10.2: Crosstalk Suppression by Image Processing in 3D Display. SID Symposium Digest of Technical Papers. 41(1). 124–127. 13 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.

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