3 citations · 4 across the 12 of their papers we have counts for
8 papers · 1 filter
Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning
Yuqi Li, Yuedong Tan, Huiran Duan +7
Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy computational burden of sta…
GaitKD: A Universal Decoupled Distillation Framework for Efficient Gait Recognition
Yuqi Li, Qian Zhou, Huiran Duan +5
Gait recognition is an attractive biometric modality for long-range and contact-free identification, but high-performing gait models often rely on deep and computationally expensiv…
MMT-ARD: Multimodal Multi-Teacher Adversarial Distillation for Robust Vision-Language Models
Yuqi Li, Junhao Dong, Chuanguang Yang +5
Vision-Language Models (VLMs) are increasingly deployed in safety-critical applications, making their adversarial robustness a crucial concern. While adversarial knowledge distilla…
Asymmetric Cross-Modal Knowledge Distillation: Bridging Modalities with Weak Semantic Consistency
Riling Wei, Kelu Yao, Chuanguang Yang +3
Cross-modal Knowledge Distillation has demonstrated promising performance on paired modalities with strong semantic connections, referred to as Symmetric Cross-modal Knowledge Dist…
AMMKD: Adaptive Multimodal Multi-teacher Distillation for Lightweight Vision-Language Models
Yuqi Li, Chuanguang Yang, Junhao Dong +6
The success of large-scale visual language pretraining (VLP) models has driven widespread adoption of image-text retrieval tasks. However, their deployment on mobile devices remain…
MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation
Weilun Feng, Chuanguang Yang, Haotong Qin +10
Diffusion models have demonstrated remarkable performance on vision generation tasks. However, the high computational complexity hinders its wide application on edge devices. Quant…
Enhancing Image Generation Fidelity via Progressive Prompts
Zhen Xiong, Yuqi Li, Chuanguang Yang +4
The diffusion transformer (DiT) architecture has attracted significant attention in image generation, achieving better fidelity, performance, and diversity. However, most existing…
Prototype-Driven Multi-Feature Generation for Visible-Infrared Person Re-identification
Jiarui Li, Zhen Qiu, Yilin Yang +3
The primary challenges in visible-infrared person re-identification arise from the differences between visible (vis) and infrared (ir) images, including inter-modal and intra-modal…