Unnat Jain

781 total citations
11 papers, 165 citations indexed

About

Unnat Jain is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Unnat Jain has authored 11 papers receiving a total of 165 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Unnat Jain's work include Multimodal Machine Learning Applications (8 papers), Human Pose and Action Recognition (3 papers) and Reinforcement Learning in Robotics (3 papers). Unnat Jain is often cited by papers focused on Multimodal Machine Learning Applications (8 papers), Human Pose and Action Recognition (3 papers) and Reinforcement Learning in Robotics (3 papers). Unnat Jain collaborates with scholars based in United States, Canada and Jamaica. Unnat Jain's co-authors include Alexander G. Schwing, Ziyu Zhang, Lili Chen, Shikhar Bahl, Russell Mendonca, Deepak Pathak, Anne Lynn S. Chang, Svetlana Lazebnik, Aniruddha Kembhavi and Luca Weihs and has published in prestigious journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV), arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Unnat Jain

11 papers receiving 159 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Unnat Jain United States	6	123	98	30	7	5	11	165
Nicholas FitzGerald United States	6	116 0.9×	221 2.3×	14 0.5×	3 0.4×	4 0.8×	14	268
Siddharth Karamcheti United States	7	42 0.3×	73 0.7×	29 1.0×	5 0.7×	6 1.2×	11	114
Qiaozi Gao United States	8	73 0.6×	113 1.2×	14 0.5×	6 0.9×	4 0.8×	11	144
Jiaxi Wu China	6	95 0.8×	87 0.9×	15 0.5×	12 1.7×	4 0.8×	13	157
Samyak Datta United States	4	205 1.7×	137 1.4×	12 0.4×	23 3.3×	8 1.6×	4	233
Ayush Shrivastava United States	7	84 0.7×	97 1.0×	9 0.3×	15 2.1×	3 0.6×	12	158
Quan Vuong United States	7	49 0.4×	52 0.5×	47 1.6×	3 0.4×	3 0.6×	15	124
Shaobo Hou United Kingdom	5	64 0.5×	53 0.5×	35 1.2×	4 0.6×	4 0.8×	7	122
Jay Zhangjie Wu Singapore	4	202 1.6×	43 0.4×	31 1.0×	2 0.3×	3 0.6×	8	243
Muhannad Alomari United Kingdom	7	68 0.6×	66 0.7×	21 0.7×	5 0.7×	4 0.8×	13	120

Countries citing papers authored by Unnat Jain

Since Specialization

Citations

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

Fields of papers citing papers by Unnat Jain

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Unnat Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Unnat Jain. A scholar is included among the top collaborators of Unnat Jain 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 Unnat Jain. Unnat Jain 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:

11 of 11 papers shown

1.

Chowdhary, Girish, et al.. (2024). Exploitation-Guided Exploration for Semantic Embodied Navigation. 2901–2908. 2 indexed citations

2.

Jain, Unnat, et al.. (2024). MOPA: Modular Object Navigation with PointGoal Agents. 5751–5761. 2 indexed citations

3.

Patel, Dhruvesh, et al.. (2023). Pretrained Language Models as Visual Planners for Human Assistance. 15256–15268. 3 indexed citations

4.

Bahl, Shikhar, Russell Mendonca, Lili Chen, Unnat Jain, & Deepak Pathak. (2023). Affordances from Human Videos as a Versatile Representation for Robotics. 1–13. 45 indexed citations

5.

Jain, Unnat, et al.. (2021). Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 4018–4028. 25 indexed citations

6.

Jain, Unnat, et al.. (2021). Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agents. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15953–15963. 1 indexed citations

7.

Jain, Unnat, et al.. (2021). GridToPix: Training Embodied Agents with Minimal Supervision. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15121–15131. 10 indexed citations

8.

Jain, Unnat, et al.. (2021). GridToPix: Training Embodied Agents with Minimal Supervision. arXiv (Cornell University). 15141–15151. 2 indexed citations

9.

Jain, Unnat, et al.. (2019). TAB-VCR: Tags and Attributes based VCR Baselines. Neural Information Processing Systems. 32. 15615–15628. 6 indexed citations

10.

Jain, Unnat, Ziyu Zhang, & Alexander G. Schwing. (2017). Creativity: Generating Diverse Questions Using Variational Autoencoders. 5415–5424. 64 indexed citations

11.

Jain, Unnat, et al.. (2000). Centre-state relations. 5 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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