Chuanguang Yang

RSICCLLM: A Multimodal Large Language Model for Remote Sensing Image Change Captioning

Yelin Wang, Zijia Song, Shuo Ye +6

Remote Sensing Image Change Captioning (RSICC) aims to describe changes between bi-temporal remote sensing images and holds significant research and application value. However, mos…

Not All Tasks Quantize Equally: Fisher-Guided Quantization for Visual Geometry Transformer

Yipu Zhang, Jintao Cheng, Weilun Feng +5

Feed-forward 3D reconstruction models, represented by Visual Geometry Grounded Transformer (VGGT), jointly predict multiple visual geometry tasks such as depth estimation, camera p…

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…

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

Jiatong Li, Zheng Chen, Kai Liu +91

This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge…

The Fourth Challenge on Image Super-Resolution ( $\times$ 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 ( $\times$ 4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

Teacher-Guided Student Self-Knowledge Distillation Using Diffusion Model

Yu Wang, Chuanguang Yang, Zhulin An +6

Existing Knowledge Distillation (KD) methods often align feature information between teacher and student by exploring meaningful feature processing and loss functions. However, due…

MultiAnimate: Pose-Guided Image Animation Made Extensible

Yingcheng Hu, Haowen Gong, Chuanguang Yang +3

Pose-guided human image animation aims to synthesize realistic videos of a reference character driven by a sequence of poses. While diffusion-based methods have achieved remarkable…

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…

Parameterized Prompt for Incremental Object Detection

Zijia An, Boyu Diao, Ruiqi Liu +5

Recent studies have demonstrated that incorporating trainable prompts into pretrained models enables effective incremental learning. However, the application of prompts in incremen…

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…

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…

S $^{2}$ Q-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.…

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…

Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers

Weilun Feng, Chuanguang Yang, Haotong Qin +8

Diffusion transformers (DiT) have demonstrated exceptional performance in video generation. However, their large number of parameters and high computational complexity limit their…

PrePrompt: Predictive prompting for class incremental learning

Libo Huang, Zhulin An, Chuanguang Yang +5

Class Incremental Learning (CIL) based on pre-trained models offers a promising direction for open-world continual learning. Existing methods typically rely on correlation-based st…

Multi-party Collaborative Attention Control for Image Customization

Han Yang, Chuanguang Yang, Qiuli Wang +4

The rapid advancement of diffusion models has increased the need for customized image generation. However, current customization methods face several limitations: 1) typically acce…

Efficient Continual Learning through Frequency Decomposition and Integration

Ruiqi Liu, Boyu Diao, Libo Huang +4

Continual learning (CL) aims to learn new tasks while retaining past knowledge, addressing the challenge of forgetting during task adaptation. Rehearsal-based methods, which replay…

Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition

Chuanguang Yang, Xinqiang Yu, Han Yang +4

Multi-teacher Knowledge Distillation (KD) transfers diverse knowledge from a teacher pool to a student network. The core problem of multi-teacher KD is how to balance distillation…

ECG-guided individual identification via PPG

Riling Wei, Hanjie Chen, Kelu Yao +3

Photoplethsmography (PPG)-based individual identification aiming at recognizing humans via intrinsic cardiovascular activities has raised extensive attention due to its high securi…

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models

Weilun Feng, Haotong Qin, Chuanguang Yang +7

Diffusion models have received wide attention in generation tasks. However, the expensive computation cost prevents the application of diffusion models in resource-constrained scen…

Relational Diffusion Distillation for Efficient Image Generation

Weilun Feng, Chuanguang Yang, Zhulin An +4

Although the diffusion model has achieved remarkable performance in the field of image generation, its high inference delay hinders its wide application in edge devices with scarce…