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Found 4 papers, 2 papers with code
Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network
We train one conventional and one spherical FCRN for underwater perspective and omni-directional images, respectively.
Video Contrastive Learning with Global Context
Our formulation is able to capture global context in a video, thus robust to temporal content change.
IR-MCL: Implicit Representation-Based Online Global Localization
The experiments suggest that the presented implicit representation is able to predict more accurate 2D LiDAR scans leading to an improved observation model for our particle filter-based localization.
STAIR: Semantic-Targeted Active Implicit Reconstruction
The key components of our framework are a semantic implicit neural representation and a compatible planning utility function based on semantic rendering and uncertainty estimation, enabling adaptive view planning to target objects of interest.
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