4 papers indexed
Yuang Meng, Chenyang Wu, Xianshun Liu, Chun-Le Guo, Zichen Liang, Lina Lei, et al.
Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation. Iterative methods, exemplified by RAFT, achieve high accuracy through recurrent refinement, but remain challenged by large displacements and complex motion. Diffusio…
Yao Liu, Lishen Qu, Shihao Zhou, Jie Liang, Hui Zeng, Yabin Peng, et al.
Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-quality dynamic benchmarks. Current benchmarks largely neglect dynamic scenes and lack reliable ground truth, making it difficul…
Lishen Qu, Yao Liu, Shihao Zhou, Jie Liang, Hui Zeng, Lei Zhang, et al.
Multi-exposure fusion (MEF) brings the dynamic range of conventional cameras closer to that of human vision, producing images with rich scene content. Given the large variability in scene luminance, exposure strategies often require different numbers of frames to capture the full…
Jie Liang, Marlissa Omar, Intan Farahana Kamsin
The rapid development of artificial intelligence (AI) has broken the time and space limitations of traditional classroom learning and provides vocational school students with a convenient and new forms of mobile learning supported by generative AI applications. In order to explor…