1 citations · 1 across the 14 of their papers we have counts for
16 papers
LensBridge: Frequency-Guided Compound Degradation Adaptation for Lens Aberration Correction and Veiling Glare Removal
Xiaolong Qian, Zhonghua Yi, Qi Jiang +4
Simplified optical systems often exhibit residual lens aberrations and Veiling Glare (VG), resulting in spatially varying blur and contrast reduction. Large-scale Lens Libraries (L…
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…
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…
Towards Real-world Lens Active Alignment with Unlabeled Data via Domain Adaptation
Wenyong Li, Qi Jiang, Weijian Hu +5
Active Alignment (AA) is a key technology for the large-scale automated assembly of high-precision optical systems. Compared with labor-intensive per-model on-device calibration, a…
EvDiff: Event-Based Video Reconstruction using One-Step Diffusion Models
Weilun Li, Lei Sun, Ruixi Gao +6
As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal resolution and high dynamic rang…
Learning Latent Transmission and Glare Maps for Lens Veiling Glare Removal
Xiaolong Qian, Qi Jiang, Lei Sun +8
Beyond the commonly recognized optical aberrations, the imaging performance of simplified optical systems--including single-lens and metalens designs--is often further degraded by…
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…
Large-FOV RGBD Imaging via Structured PSF Coding in a Bio-inspired Monocentric System
Zongxi Yu, Xiaolong Qian, Shaohua Gao +4
High-fidelity large-field-of-view (LFOV) 3D sensing, essential for autonomous platforms, is hindered by the coupling of anisotropic off-axis aberrations and the ill-posed nature of…
Neuro-inspired automated lens design
Yao Gao, Lei Sun, Shaohua Gao +7
The highly non-convex optimization landscape of modern lens design necessitates extensive human expertise, resulting in inefficiency and constrained design diversity. While automat…
QuaDreamer: Controllable Panoramic Video Generation for Quadruped Robots
Sheng Wu, Fei Teng, Hao Shi +4
Panoramic cameras, capturing comprehensive 360-degree environmental data, are suitable for quadruped robots in surrounding perception and interaction with complex environments. How…
Towards Dependable Optical Flow: Benchmarks for Real-World Spatiotemporal Corruptions
Zhonghua Yi, Hao Shi, Qi Jiang +5
Optical flow estimation is a fundamental task in dynamic scene understanding and computer vision. While recent deep models achieve impressive accuracy on clean benchmarks, their ro…
EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local Feature Extraction and Matching for Event-Image Data
Zhonghua Yi, Hao Shi, Qi Jiang +5
Event cameras, with high temporal resolution and high dynamic range, have limited research on the inter-modality local feature extraction and matching of event-image data. We propo…
Towards Single-Lens Controllable Depth-of-Field Imaging via Depth-Aware Point Spread Functions
Xiaolong Qian, Qi Jiang, Yao Gao +8
Controllable Depth-of-Field (DoF) imaging commonly produces amazing visual effects based on heavy and expensive high-end lenses. However, confronted with the increasing demand for…
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…
Exploring Quasi-Global Solutions to Compound Lens Based Computational Imaging Systems
Yao Gao, Qi Jiang, Shaohua Gao +3
Recently, joint design approaches that simultaneously optimize optical systems and downstream algorithms through data-driven learning have demonstrated superior performance over tr…
Representing Domain-Mixing Optical Degradation for Real-World Computational Aberration Correction via Vector Quantization
Qi Jiang, Zhonghua Yi, Shaohua Gao +8
Relying on paired synthetic data, existing learning-based Computational Aberration Correction (CAC) methods are confronted with the intricate and multifaceted synthetic-to-real dom…