Divyansh Garg

1.8k total citations · 1 hit paper
4 papers, 839 citations indexed

About

Divyansh Garg is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Computer Networks and Communications. According to data from OpenAlex, Divyansh Garg has authored 4 papers receiving a total of 839 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 2 papers in Aerospace Engineering and 1 paper in Computer Networks and Communications. Recurrent topics in Divyansh Garg's work include Advanced Vision and Imaging (3 papers), Advanced Neural Network Applications (3 papers) and Robotics and Sensor-Based Localization (2 papers). Divyansh Garg is often cited by papers focused on Advanced Vision and Imaging (3 papers), Advanced Neural Network Applications (3 papers) and Robotics and Sensor-Based Localization (2 papers). Divyansh Garg collaborates with scholars based in United States, India and Ireland. Divyansh Garg's co-authors include Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei‐Lun Chao, Yan Wang, Serge Belongie, Yan Wang, Yurong You, Rui Qian and V. Subramaniyaswamy and has published in prestigious journals such as Neural Information Processing Systems and 2021 Innovations in Power and Advanced Computing Technologies (i-PACT).

In The Last Decade

Divyansh Garg

4 papers receiving 808 citations

Hit Papers

Pseudo-LiDAR From Visual Depth Estimation: Bridging the G... 2019 2026 2021 2023 2019 200 400 600

Peers

Divyansh Garg
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 743
  • Aerospace Engineering 415
  • Automotive Engineering 134
  • Media Technology 102
  • Environmental Engineering 80
Replace Ziyu Zhang with:
Ziyu Zhang China
Rui Qian China
Xinzhu Ma China
Yohann Cabon South Korea
Qingqiu Huang China
Zeyu Hu China
Rareş Ambruş United States
Zizhang Wu China
Xiao Song China
Takashi Naito Japan
Ziyu Zhang China View profile →
Citations per field, relative to Divyansh Garg
Divyansh Garg · 1×
Citations per year, relative to Divyansh Garg
Divyansh Garg · 1×

Countries citing papers authored by Divyansh Garg

Since Specialization
Citations

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

Fields of papers citing papers by Divyansh Garg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Divyansh Garg

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

All Works

4 of 4 papers shown
# Work Indexed citations
1 3
2
Wasserstein Distances for Stereo Disparity Estimation
1
3 134
4
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving breakdown →
701

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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2026