I am Swati Jindal, a final year Ph.D. Candidate in Computer Science at the University of California, Santa Cruz, working with Prof. Roberto Manduchi. My research interests focus on the intersection of computer vision and deep learning, with a particular focus on image- and video-based gaze tracking. I was fortunate to have the opportunity to collaborate with Prof. Xin Eric Wang.
I was a Researcher at TCS Innovation Labs, India working with Dr. Gautam Shroff and Dr. Lovekesh Vig. I completed my Master's degree from Indian Institute of Technology (IIT), Hyderabad working with Prof. K Sri Rama Murty.
CGPA: 3.9/4.0
CGPA: 9.03/10
CGPA: 8.67/10
CUDA-GHR: Controllable Unsupervised Domain Adaptation for Gaze and Head Redirection
Swati Jindal, Xin Eric Wang
WACV 2023
[PDF] [Code]
Contrastive Representation Learning for Gaze Estimation
Swati Jindal, Roberto Manduchi
NeurIPS 2022, Gaze Meets ML Workshop
Best Paper Award (Spotlight)
[PDF] [Code]
Tracker/Camera Calibration for Accurate Automatic Gaze Annotation of Images and Videos
Swati Jindal, Harsimran Kaur, Roberto Manduchi
ETRA 2022
[PDF]
Rethinking Model-Based Gaze Estimation
Harsimran Kaur, Swati Jindal, Roberto Manduchi
ETRA 2022
Oral presentation
[PDF]
Deep Reader: Information extraction from Document images via relation extraction and Natural Language
Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan
ACCV 2018, IWRR workshop
[PDF]
Automatic Classification of Low-Resolution Chromosomal Images
Swati, Monika Sharma, Lovekes Vig
ECCV 2018, BIC workshop
[PDF]
Automatic Chromosome Classification using Deep Attention Based Sequence Learning of Chromosome Bands
Monika Sharma*, Swati*, Lovekes Vig (*equal contribution)
IJCNN 2018
[PDF]
Siamese Networks For Chromosome Classification
Swati, Gaurav Gupta, Mohit Yadav, Monika Sharma, Lovekesh Vig
ICCV 2017, BIC workshop
[PDF]
Information Extraction from Hand-Marked Industrial Inspection sheets
Gaurav Gupta, Swati, Monika Sharma, Lovekesh Vig
ICDAR 2017, CBDAR workshop
[PDF]
Winter 2023: Artificial Intelligence
Fall 2022: Machine Learning
Spring 2021: Computer Vision
Spring 2020: Computer Vision
Fall 2019: Universal Access
Winter 2016: Adaptive Signal Processing
Fall 2015: Probability and Random Processes