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Found 10 papers, 7 papers with code
NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods
To address the issues above, we propose NeRF-NQA, the first no-reference quality assessment method for densely-observed scenes synthesized from the NVS and NeRF variants.
EvRepSL: Event-Stream Representation via Self-Supervised Learning for Event-Based Vision
However, most of the state-of-the-art event-stream representations are manually designed and the quality of these representations cannot be guaranteed due to the noisy nature of event-streams.
Beyond Gaussians: Fast and High-Fidelity 3D Splatting with Linear Kernels
Recent advancements in 3D Gaussian Splatting (3DGS) have substantially improved novel view synthesis, enabling high-quality reconstruction and real-time rendering.
Efficient Multi-disparity Transformer for Light Field Image Super-resolution
This paper presents the Multi-scale Disparity Transformer (MDT), a novel Transformer tailored for light field image super-resolution (LFSR) that addresses the issues of computational redundancy and disparity entanglement caused by the indiscriminate processing of sub-aperture images inherent in conventional methods.
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.
