activity
20232026
most citedFederated Knowledge Distillation for Multi-Model Architectures Lithography Hotspot Detection

1 citations · 1 across the 16 of their papers we have counts for

collaborators

18 papers

cs.CV2026

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…

cs.CV2026

Rethinking Layer-Wise Information Allocation for Vision Foundation Model Adaptation

Yuqi Li, Xi Xiao, Yunbei Zhang +6

Vision foundation models are increasingly reused as frozen backbones for downstream visual recognition, making parameter-efficient adaptation a central problem. Prompt-based adapta…

cs.CV2026

Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation

Mingqiang Wu, Weilun Feng, Zhefeng Zhang +8

Autoregressive video diffusion models enable open-ended generation through local attention and KV caching. However, existing training-free long-video optimization methods mainly fo…

cs.CV2026

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…

cs.CV2026

The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen, Kai Liu, Jingkai Wang +150

This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

cs.CV2026

WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching

Weilun Feng, Guoxin Fan, Haotong Qin +10

Diffusion-based world models have shown strong potential for unified world simulation, but the iterative denoising remains too costly for interactive use and long-horizon rollouts.…

cs.CV2026

Fast-SAM3D: 3Dfy Anything in Images but Faster

Weilun Feng, Mingqiang Wu, Zhiliang Chen +10

SAM3D enables scalable, open-world 3D reconstruction from complex scenes, yet its deployment is hindered by prohibitive inference latency. In this work, we conduct the \textbf{firs…

cs.CV2025

QuantSparse: Comprehensively Compressing Video Diffusion Transformer with Model Quantization and Attention Sparsification

Weilun Feng, Chuanguang Yang, Haotong Qin +8

Diffusion transformers exhibit remarkable video generation capability, yet their prohibitive computational and memory costs hinder practical deployment. Model quantization and atte…

cs.CV2025

Quantized Visual Geometry Grounded Transformer

Weilun Feng, Haotong Qin, Mingqiang Wu +8

Learning-based 3D reconstruction models, represented by Visual Geometry Grounded Transformers (VGGTs), have made remarkable progress with the use of large-scale transformers. Their…

cs.CV2025

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…

cs.CV2025

SQ-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation

Weilun Feng, Haotong Qin, Chuanguang Yang +7

Diffusion transformers have emerged as the mainstream paradigm for video generation models. However, the use of up to billions of parameters incurs significant computational costs.…

cs.LG2025

Frequency-Aligned Knowledge Distillation for Lightweight Spatiotemporal Forecasting

Yuqi Li, Chuanguang Yang, Hansheng Zeng +5

Spatiotemporal forecasting tasks, such as traffic flow, combustion dynamics, and weather forecasting, often require complex models that suffer from low training efficiency and high…

cs.CV2025

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…

cs.CV2025

SRKD: Towards Efficient 3D Point Cloud Segmentation via Structure- and Relation-aware Knowledge Distillation

Yuqi Li, Junhao Dong, Zeyu Dong +3

3D point cloud segmentation faces practical challenges due to the computational complexity and deployment limitations of large-scale transformer-based models. To address this, we p…

cs.CV2025

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…

cs.LG2025★ 1 cited

Federated Knowledge Distillation for Multi-Model Architectures Lithography Hotspot Detection

Yuqi Li, Xingyou Lin, Yanli Li +6

As a special type of multimedia data, Lithography Hotspot Detection (LHD) training often requires stronger privacy protection than conventional multimedia data, and federated learn…

cs.CV2024

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…

cs.SD2023

Team AcieLee: Technical Report for EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023

Yuqi Li, Yizhi Luo, Xiaoshuai Hao +4

In this report, we describe the technical details of our submission to the EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023, by Team "AcieLee" (username: Yuqi\_Li). T…