EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
Towards real- istic data generation for real-world super-resolution
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EventGait is a dual-stream spiking and cross-modal framework for event-based gait recognition that matches or exceeds RGB methods in normal conditions and significantly outperforms them in low light, supported by new synthetic event gait benchmarks.
A new dataset with high-fidelity close-up garment images and full/close-up try-on videos plus the VGID metric enables better texture and structure preservation in high-resolution video virtual try-on.
citing papers explorer
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Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset
EIC-LIE uses an event-illumination collaborative module and illumination-aware event filter plus a new real-world dataset to improve low-light image enhancement over prior methods.
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EventGait: Towards Robust Gait Recognition with Event Streams
EventGait is a dual-stream spiking and cross-modal framework for event-based gait recognition that matches or exceeds RGB methods in normal conditions and significantly outperforms them in low light, supported by new synthetic event gait benchmarks.
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Eevee: Towards Close-up High-resolution Video-based Virtual Try-on
A new dataset with high-fidelity close-up garment images and full/close-up try-on videos plus the VGID metric enables better texture and structure preservation in high-resolution video virtual try-on.