Research

My interests broadly lie in the fields of computer vision, machine learning and with applications in problems related to data-efficient learning.

Publications

• HOLMES: Hyper-Relational Knowledge Graphs for Multi-hop Question Answering using LLMs
  Pranoy Panda, Ankush Agarwal, Chaitanya Devaguptapu, Manohar Kaul, Prathosh A P
  In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)
  arXiv

• Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation
  Siddharth Katageri^†, Arkadipta De^†, Chaitanya Devaguptapu^†, VSSV Prasad, Charu Sharma, Manohar Kaul
  In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA. 2024
  Oral (Top ~7% of all the accepted papers)
  ^{† Equal Contribution}
  arXiv Code Project Page

• Partial Label Learning meets Active Learning: Enhancing Annotation Efficiency through Binary Questioning
  Shivangana Rawat, Chaitanya Devaguptapu, Vineeth N Balasubramanian
  Workshop on Artificial Intelligence & Human-Computer Interaction, ICML-2023
  Published PDF Poster Video

• On Adversarial Robustness: A Neural Architecture Search perspective
  Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Pulkit Gopalani, Vineeth N Balasubramanian Workshop on Adversarial Robustness in the Real World, IEEE/CVF International Conference on Computer Vision (ICCV’21) Also accepted at ICLR-21 workshops as Contributed talk and Spotlight
  arXiv Code Poster Workshop

• On Initial Pools for Deep Active Learning
  Akshay L Chandra^†, S.V. Desai^†, Chaitanya Devaguptapu^†, Vineeth N Balasubramanian
  Preregistration Workshop at NeurIPS 2020 (PMLR Volume 148)
  ^{† Equal Contribution}
  arXiv Code Poster Workshop

• Borrow From Anywhere: Pseudo Multi-Modal Object Detection in Thermal Imagery
  Chaitanya Devaguptapu, Ninad Akolekar, Manuj M Sharma, Vineeth N Balasubramanian
  Workshop on Perception beyond visible spectrum, IEEE/CVF International Conference on Computer Vision and Pattern recognition (CVPR’19)
  (Spotlight, Among top 6 of the 30 accepted papers)
  arXiv Code Poster Workshop

Pre-prints

• ∆-Patching: A Framework for Rapid Adaptation of Pre-trained Convolutional Networks without Base Performance Loss
  Chaitanya Devaguptapu, Samarth Sinha, K J Joseph, Vineeth N Balasubramanian, Animesh Garg
  Under Review
  arXiv

• Regularizing Self-Supervised Learning on Small Datasets via Semantic Graph Consistency
  Chaitanya Devaguptapu, Sumukh Aithal, Yamada Moyuru, Manohar Kaul
  Under Review
  

Miscellaneous

• Object Detection in Low-Resolution Thermal Imagery - Enhanced the performance of object detection in thermal images by increasing the resolution of 160 x 120 images using super resolution and various deep learning based image interpolation techniques. This was a joint project with DRDO, Government of India

• Indian patent - Chaitanya Devaguptapu, Ninad Akolekar, Manuj M Sharma, Vineeth N Balasubramanian, A Methodology for Transfer of Knowledge from Data-Rich Domains for Thermal Image Processing, Indian Patent Application No. 202011032663 (filed in Aug 2020)