3 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
AdaptiveAE: An Adaptive Exposure Strategy for HDR Capturing in Dynamic Scenes
Tianyi Xu, Fan Zhang, Boxin Shi +2
Mainstream high dynamic range imaging techniques typically rely on fusing multiple images captured with different exposure setups (shutter speed and ISO). A good balance between sh…
S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion
Yujin Wang, Jiarui Wu, Yichen Bian +2
The generalization of learning-based high dynamic range (HDR) fusion is often limited by the availability of training data, as collecting large-scale HDR images from dynamic scenes…
EGVD: Event-Guided Video Diffusion Model for Physically Realistic Large-Motion Frame Interpolation
Ziran Zhang, Xiaohui Li, Yihao Liu +4
Video frame interpolation (VFI) in scenarios with large motion remains challenging due to motion ambiguity between frames. While event cameras can capture high temporal resolution…
Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
Jiarui Wu, Yujin Wang, Lingen Li +2
Photo finishing tuning aims to automate the manual tuning process of the photo finishing pipeline, like Adobe Lightroom or Darktable. Previous works either use zeroth-order optimiz…
UltraFusion: Ultra High Dynamic Imaging using Exposure Fusion
Zixuan Chen, Yujin Wang, Xin Cai +5
Capturing high dynamic range (HDR) scenes is one of the most important issues in camera design. Majority of cameras use exposure fusion, which fuses images captured by different ex…