21 citations · 59 across the 10 of their papers we have counts for
23 papers
GazePrior: Zero-Shot AR/VR Eye Tracking via Learned 3D Gaze Reconstruction
Corentin Dumery, David Colmenares, Alexander Fix +3
Eye tracking (ET) is a foundational technology for advanced AR/VR applications. However, training ET models for every new ET device is challenging: real data collection is costly a…
Rapidly deploying on-device eye tracking by distilling visual foundation models
Cheng Jiang, Jogendra Kundu, David Colmenares +4
Eye tracking (ET) plays a critical role in augmented and virtual reality applications. However, rapidly deploying high-accuracy, on-device gaze estimation for new products remains…
Digitally Prototype Your Eye Tracker: Simulating Hardware Performance using 3D Synthetic Data
Esther Y. H. Lin, Yimin Ding, Jogendra Kundu +3
Eye tracking (ET) is a key enabler for Augmented and Virtual Reality (AR/VR). Prototyping new ET hardware requires assessing the impact of hardware choices on eye tracking performa…
Aligning Non-Causal Factors for Transformer-Based Source-Free Domain Adaptation
Sunandini Sanyal, Ashish Ramayee Asokan, Suvaansh Bhambri +4
Conventional domain adaptation algorithms aim to achieve better generalization by aligning only the task-discriminative causal factors between a source and target domain. However,…
Subsidiary Prototype Alignment for Universal Domain Adaptation
Jogendra Nath Kundu, Suvaansh Bhambri, Akshay Kulkarni +3
Universal Domain Adaptation (UniDA) deals with the problem of knowledge transfer between two datasets with domain-shift as well as category-shift. The goal is to categorize unlabel…
Non-Local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation
Jogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi +4
Available 3D human pose estimation approaches leverage different forms of strong (2D/3D pose) or weak (multi-view or depth) paired supervision. Barring synthetic or in-studio domai…