Yingtie Lei — accepted AI-conference papers

2026

ProMist-5K: A Comprehensive Dataset for Digital Emulation of Cinematic Pro-Mist Filter Effects

Yingtie Lei, Zimeng Li, Chi-Man Pun, Wangyu Wu, Junke Yang, Xuhang Chen

ICASSP 2026poster

Pro-Mist filters are widely used in cinematography for their ability to create soft halation, lower contrast, and produce a distinctive, atmospheric style. These effects are difficult to reproduce digitally due to the complex behavior of light diffusion. We present ProMist-5K, a dataset designed to…

Cited by 0 Source ↗PDF ↗Scholar ↗

2026

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models

Jingxuan Zhang, Yunta Hsieh, Zhongwei Wan, Haokun Lin, Xin Wang, Ziqi Wang +2

CVPR 2026

Vision-language-action (VLA) models unify perception, language, and control for embodied agents but face significant challenges in practical deployment due to rapidly increasing compute and memory demands, especially as models scale to longer horizons and larger backbones. To address these bottlenec

Cited by 0 Source ↗code ↗Scholar ↗