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NeRF-In: Free-Form NeRF Inpainting with RGB-D Priors
In this paper, we introduce the first framework that enables users to remove unwanted objects or retouch undesired regions in a 3D scene represented by a pre-trained NeRF without any category-specific data and training.
Reducing the Deployment-Time Inference Control Costs of Deep Reinforcement Learning Agents via an Asymmetric Architecture
Deep reinforcement learning (DRL) has been demonstrated to provide promising results in several challenging decision making and control tasks.
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