DachunKai/EvTexture
Event-driven video super-resolution model using deep learning to enhance texture details in videos.
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This repository implements EvTexture, a deep learning approach for video super-resolution that leverages event-camera data. Event cameras capture per-pixel brightness changes asynchronously rather than fixed-frame exposures, providing high temporal resolution. The model uses this event data to reconstruct high-resolution video frames with enhanced texture details. The work was published at ICML 2024 with a journal extension accepted to IEEE TPAMI 2026.
Frequently asked
- What is DachunKai/EvTexture?
- Event-driven video super-resolution model using deep learning to enhance texture details in videos.
- Is EvTexture open source?
- Yes — DachunKai/EvTexture is open source, released under the Apache-2.0 license.
- What language is EvTexture written in?
- DachunKai/EvTexture is primarily written in Python.
- How popular is EvTexture?
- DachunKai/EvTexture has 1.2k stars on GitHub.
- Where can I find EvTexture?
- DachunKai/EvTexture is on GitHub at https://github.com/DachunKai/EvTexture.