Robust 2.5D Feature Matching in Light Fields via a Learnable Parameterized Depth-Degraded Projection
Abstract: Due to the loss of 3D information, accurate and robust 2D image feature matching remains challenging for many computer vision applications. This paper introduces a 2.5D feature that uses the ...
Abstract: The rapid advancements of heterogeneous 2.5D systems demand innovative solutions to optimize chiplet placement, ensuring a balance between thermal management, performance, and connectivity.
Practical workflows using Unity-MCP's 52 tools, 48 prompts, and 1 resource. All examples show what you can ask your AI client to do once Unity-MCP is connected. "Create a new scene called 'Level01', ...
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