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Exploring Optical Flow Challenges and Solutions
This chapter delves into the team's exploration of optical flow within different research papers, addressing challenges such as noise, high dynamic range, and motion information to enhance image quality. The discussion includes methodologies for extracting valuable information from limited optical flow datasets, creating intermediate frames, and improving accuracy through self-cleaning iterations and regression focal loss. The chapter also examines innovative approaches from conference papers focusing on optical flow augmentation and low latency neural stereo streaming, emphasizing the importance of stereo aware compression models for efficient data processing on mobile devices.