Yung-Hui Li

Density-Assisted Adaptive Alignment Network for Video Individual Counting

Towards Robust Calibration Dataset for Domain-General Mixture of Experts Pruning

Post-training expert pruning is a promising deployment technique for Mixture-of-Experts (MoE) models. The calibration set is an integral part of the pruning process, however, its correlation with evaluation performance is largely misunderstood and unintuitive. In this work, we present an empirical study of the robustne...

Optimizing Fidelity-Perception Tradeoff via Large Vision–Language Model Prior for Image Compression

Current neural image compression (NIC) methods primarily focus on signal fidelity optimization. While perceptually optimized codecs can generate decoded images that better align with human visual preferences at equivalent bitrates, they raise authenticity concerns due to potential deviations from the original content....

Uncertainty-Guided Adaptive Knowledge Distillation for Lightweight Cross-Domain Object Detection

This article introduces Uncertainty-Guided Adaptive Knowledge Distillation (UGAKD), a novel framework designed to enhance UDA while simultaneously reducing model size through targeted knowledge distillation and proposing a two-stage, difficulty-aware training scheme to facilitate learning.