most citedLaSe-E2V: Towards Language-guided Semantic-Aware Event-to-Video Reconstruction

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cs.CV2026

TransText: Alpha-as-RGB Representation for Transparent Text Animation

Fei Zhang, Zijian Zhou, Bohao Tang +9

We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic v…

cs.CV2024

EvLight++: Low-Light Video Enhancement with an Event Camera: A Large-Scale Real-World Dataset, Novel Method, and More

Kanghao Chen, Guoqiang Liang, Hangyu Li +2

Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence…

cs.CV2024

A General Framework to Boost 3D GS Initialization for Text-to-3D Generation by Lexical Richness

Lutao Jiang, Hangyu Li, Lin Wang

Text-to-3D content creation has recently received much attention, especially with the prevalence of 3D Gaussians Splatting. In general, GS-based methods comprise two key stages: in…

cs.CV2024

FlowDreamer: Exploring High Fidelity Text-to-3D Generation via Rectified Flow

Hangyu Li, Xiangxiang Chu, Dingyuan Shi +1

Recent advances in text-to-3D generation have made significant progress. In particular, with the pretrained diffusion models, existing methods predominantly use Score Distillation…

cs.CV20241 cited

LaSe-E2V: Towards Language-guided Semantic-Aware Event-to-Video Reconstruction

Kanghao Chen, Hangyu Li, JiaZhou Zhou +2

Event cameras harness advantages such as low latency, high temporal resolution, and high dynamic range (HDR), compared to standard cameras. Due to the distinct imaging paradigm shi…

cs.CV2024

Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach

Guoqiang Liang, Kanghao Chen, Hangyu Li +2

Event camera has recently received much attention for low-light image enhancement (LIE) thanks to their distinct advantages, such as high dynamic range. However, current research i…