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Found 6 papers, 5 papers with code
E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning
In this work, we propose \textbf{E2HQV}, a novel E2V paradigm designed to produce high-quality video frames from events.
LFACon: Introducing Anglewise Attention to No-Reference Quality Assessment in Light Field Space
In this paper, we propose a novel concept of "anglewise attention" by introducing a multihead self-attention mechanism to the angular domain of an LFI.
Texture-enhanced Light Field Super-resolution with Spatio-Angular Decomposition Kernels
Despite the recent progress in light field super-resolution (LFSR) achieved by convolutional neural networks, the correlation information of light field (LF) images has not been sufficiently studied and exploited due to the complexity of 4D LF data.
Efficient Light Field Reconstruction via Spatio-Angular Dense Network
As an image sensing instrument, light field images can supply extra angular information compared with monocular images and have facilitated a wide range of measurement applications.
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
We present a multi-agent actor-critic method that aims to implicitly address the credit assignment problem under fully cooperative settings.
Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues
Specifically, our end-to-end model first synthesizes a set of intermediate novel sub-aperture images (SAIs) by exploring the coarse characteristics of the sparsely-sampled LF input with spatial-angular alternating convolutions.
