- Focus Longer to See Better: Recursively Refined Attention for Fine-Grained Image Classification. Prateek Shroff, Tianlong Chen, Yunchao Wei, Zhangyang Wang
- Color-Constrained Dehazing Model. Shengdong Zhang, Yue Wu, Yuanjie Zhao, Zuomin Cheng, Wenqi Ren
- VDFlow: Joint Learning for Optical Flow and Video Deblurring. Yanyang Yan1, Qingbo Wu1, Bo Xu, Jingang Zhang, Wenqi Ren
- A Point Light Source Interference Removal Method for Image Dehazing. Yanyang Yan, Shengdong Zhang, Mingye Ju, Wenqi Ren, Rui Wang, Yuanfang Guo
Submission GuidelinesOriginal high-quality contributions are solicited on the following topics:
- Novel algorithms for robust object detection, segmentation or recognition on outdoor mobility platforms, such as UAVs, gliders, autonomous cars, outdoor robots, etc.
- Novel algorithms for robust object detection and/or recognition in the presence of one or more real-world adverse conditions, such as haze, rain, snow, hail, dust, underwater, low-illumination, low resolution, etc.
- The potential models and theories for explaining, quantifying, and optimizing the mutual influence between the low-level computational photography (image reconstruction, restoration, or enhancement) tasks and various high-level computer vision tasks.
- Novel physically grounded and/or explanatory models, for the underlying degradation and recovery processes, of real-world images going through complicated adverse visual conditions.
- Novel evaluation methods and metrics for image restoration and enhancement algorithms, with a particular emphasis on no-reference metrics, since for most real outdoor images with adverse visual conditions it is hard to obtain any clean “ground truth” to compare with.
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