EvDiG: Event-guided Direct and Global Components Separation
Xinyu Zhou, Peiqi Duan, Boyu Li, Chu Zhou, Chao Xu, Boxin Shi
Abstract
Separating the direct and global components of a scene aids in shape recovery and basic material understanding. Conventional methods capture multiple frames under high frequency illumination patterns or shadows, requiring the scene to keep stationary during the image acquisition process. Single-frame methods simplify the capture procedure but yield lower-quality separation results. In this paper, we leverage the event camera to facilitate the separation of direct and global components, enabling video-rate separation of high quality. In detail, we adopt an event camera to record rapid illumination changes caused by the shadow of a line occluder sweeping over the scene, and reconstruct the coarse separation results through event accumulation. We then design a network to resolve the noise in the coarse sep-aration results and restore color information. A real-world dataset is collected using a hybrid camera system for network training and evaluation. Experimental results show superior performance over state-of-the-art methods.
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Cited by top-tier papers4
- EventUPS: Uncalibrated Photometric Stereo Using an Event CameraJinxiu Liang, Bohan Yu, Siqi Yang, Haotian Zhuang et al.ICCV 2025 · 4 citations
- Dual Band Thermal Videography: Separating Time-Varying Reflection and Emission Near Ambient ConditionsSriram Narayanan, Mani Ramanagopal, Srinivasa G. NarasimhanCVPR 2026 · 1 citation
- Spatio-Spectral Pattern Illumination for Direct and Indirect Separation from a Single Hyperspectral ImageShin Ishihara, Imari SatoICCV 2025 · 1 citation
- EventPSR: Surface Normal and Reflectance Estimation from Photometric Stereo Using an Event CameraBohan Yu, Jin Han, Boxin Shi, Imari SatoCVPR 2025
Builds on7
- Restormer: Efficient Transformer for High-Resolution Image RestorationSyed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat et al.CVPR 2022 · 3,348 citations
- End-to-End Learning of Representations for Asynchronous Event-Based DataDaniel Gehrig, Antonio Loquercio, Konstantinos G. Derpanis, Davide ScaramuzzaICCV 2019 · 427 citations
- High-fidelity Event-Radiance Recovery via Transient Event FrequencyJin Han, Yuta Asano, Boxin Shi, Yinqiang Zheng et al.CVPR 2023
- Event-Based Bispectral Photometry Using Temporally Modulated IlluminationTsuyoshi Takatani, Yuzuha Ito, Ayaka Ebisu, Yinqiang Zheng et al.CVPR 2021
- Indoor Lighting Estimation Using an Event CameraZehao Chen, Qian Zheng, Peisong Niu, Huajin Tang et al.CVPR 2021
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