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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…
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…
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…
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…