Raghav Goyal
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Human-Computer Interaction top 5%
- Endocrinology, Diabetes and Metabolism
- Co-authors
- Valentin HaenelSamira Ebrahimi KahouP.N. YianilosIngo BaxJoanna MaterzyńskaChristian ThurauIngo FruendRoland Memisevic
- Topics
- Multimodal Machine Learning Applications (2 papers)Human Pose and Action Recognition (2 papers)Speech and dialogue systems (1 paper)
- Journals
- BioengineeringInternational Conference on Learning RepresentationsInternational Conference on Computational Linguistics
In The Last Decade
Raghav Goyal
4 papers receiving 771 citations
Hit Papers
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 719
- Artificial Intelligence 438
- Biomedical Engineering 145
- Human-Computer Interaction 66
- Endocrinology, Diabetes and Metabolism 43
Countries citing papers authored by Raghav Goyal
This map shows the geographic impact of Raghav Goyal'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 Raghav Goyal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raghav Goyal more than expected).
Fields of papers citing papers by Raghav Goyal
This network shows the impact of papers produced by Raghav Goyal. 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 Raghav Goyal. The network helps show where Raghav Goyal may publish in the future.
Co-authorship network of co-authors of Raghav Goyal
This figure shows the co-authorship network connecting the top 25 collaborators of Raghav Goyal. A scholar is included among the top collaborators of Raghav Goyal 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 Raghav Goyal. Raghav Goyal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | Evaluating visual "common sense" using fine-grained classification and captioning tasks. | 0 |
| 4 | The “Something Something” Video Database for Learning and Evaluating Visual Common Sensebreakdown → | 772 |
| 5 | Natural Language Generation through Character-based RNNs with Finite-state Prior Knowledge | 7 |
About Raghav Goyal
Raghav Goyal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience, having authored 5 papers that have together received 790 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers) and Speech and dialogue systems (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (719 citations), Artificial Intelligence (438 citations) and Human-Computer Interaction (66 citations). Raghav Goyal has collaborated with scholars based in Hong Kong, India and Canada. Frequent co-authors include Valentin Haenel, Samira Ebrahimi Kahou, P.N. Yianilos, Ingo Bax, Joanna Materzyńska, Christian Thurau, Ingo Fruend, Roland Memisevic, Vincent Michalski and Heuna Kim. Their work appears in journals such as Bioengineering, International Conference on Learning Representations and International Conference on Computational Linguistics.
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.