97 citations · 181 across the 12 of their papers we have counts for
12 papers
Boosting Semantic Segmentation with Semantic Boundaries
Haruya Ishikawa, Yoshimitsu Aoki
In this paper, we present the Semantic Boundary Conditioned Backbone (SBCB) framework, a simple yet effective training framework that is model-agnostic and boosts segmentation perf…
FindView: Precise Target View Localization Task for Look Around Agents
Haruya Ishikawa, Yoshimitsu Aoki
With the increase in demands for service robots and automated inspection, agents need to localize in its surrounding environment to achieve more natural communication with humans b…
Fast Event-based Optical Flow Estimation by Triplet Matching
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that…
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-o…
Secrets of Event-Based Optical Flow
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras respond to scene dynamics and offer advantages to estimate motion. Following recent image-based deep-learning achievements, optical flow estimation methods for event…
Event Collapse in Contrast Maximization Frameworks
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Contrast maximization (CMax) is a framework that provides state-of-the-art results on several event-based computer vision tasks, such as ego-motion or optical flow estimation. Howe…