collaborators

7 papers

cs.CV2026

Label-Free Target-Domain Adaptation for Unconstrained Event-Image Feature Matching via Dual-Stage Distillation

Zhonghua Yi, Hao Shi, Qi Jiang +3

Building pixel-level correspondence between event and image data is a fundamental task for multi-sensor systems. However, existing cross-modal matching methods are largely restrict…

eess.IV2026

Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priors

Xiaolong Qian, Qi Jiang, Yao Gao +8

Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by training a universal neural network, demons…

cs.CV2026

Watching Movies Like a Human: Egocentric Emotion Understanding for Embodied Companions

Ze Dong, Hao Shi, Zejia Gao +3

Embodied robotic agents often perceive movies through an egocentric screen-view interface rather than native cinematic footage, introducing domain shifts such as viewpoint distorti…

cs.CV2026

Towards Universal Computational Aberration Correction in Photographic Cameras: A Comprehensive Benchmark Analysis

Xiaolong Qian, Qi Jiang, Yao Gao +5

Prevalent Computational Aberration Correction (CAC) methods are typically tailored to specific optical systems, leading to poor generalization and labor-intensive re-training for n…

cs.LG2026

OPTIAGENT: A Physics-Driven Agentic Framework for Automated Optical Design

Yuyu Geng, Lei Sun, Yao Gao +6

Optical design is the process of configuring optical elements to precisely manipulate light for high-fidelity imaging. It is inherently a highly non-convex optimization problem tha…

physics.optics2026

OmniLens: Towards Universal Lens Aberration Correction via LensLib-to-Specific Domain Adaptation

Qi Jiang, Yao Gao, Shaohua Gao +7

Emerging universal Computational Aberration Correction (CAC) paradigms provide an inspiring solution to light-weight and high-quality imaging with a universal model trained on a le…