24 citations · 35 across the 14 of their papers we have counts for
14 papers
ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs
Yuhao Wang, Mu Qiao, Haiwen Diao +5
Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction provides an efficient solution.…
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
Yi Zhong, Haotong Qin, Xindong Zhang +2
Low-bit post-training quantization (PTQ) is a pivotal technique for deploying Vision-Language Models (VLMs) on resource-constrained devices. However, existing PTQ methods often deg…
Towards Joint Quantization and Token Pruning of Vision-Language Models
Xinqing Li, Xin He, Xindong Zhang +3
Deploying Vision-Language Models (VLMs) under aggressive low-bit inference remains challenging because inference cost is dominated by the long visual-token prefix during prefill an…
NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results
Xin Li, Jiachao Gong, Xijun Wang +75
This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utilizes a new short-form UGC (S-…
Pretraining A Large Language Model using Distributed GPUs: A Memory-Efficient Decentralized Paradigm
Jinrui Zhang, Chaodong Xiao, Aoqi Wu +2
Pretraining large language models (LLMs) typically requires centralized clusters with thousands of high-memory GPUs (e.g., H100/A100). Recent decentralized training methods reduce…
NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +7
In this paper, we present a comprehensive overview of the NTIRE 2025 challenge on the 2nd Restore Any Image Model (RAIM) in the Wild. This challenge established a new benchmark for…
Adversarial Diffusion Compression for Real-World Image Super-Resolution
Bin Chen, Gehui Li, Rongyuan Wu +4
Real-world image super-resolution (Real-ISR) aims to reconstruct high-resolution images from low-resolution inputs degraded by complex, unknown processes. While many Stable Diffusi…
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge
Jie Liang, Radu Timofte, Qiaosi Yi +6
In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, inclu…
UniVS: Unified and Universal Video Segmentation with Prompts as Queries
Minghan Li, Shuai Li, Xindong Zhang +1
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge. This is mainly because generic category-spec…
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching
Shitong Shao, Zeyuan Yin, Muxin Zhou +2
The lightweight "local-match-global" matching introduced by SRe2L successfully creates a distilled dataset with comprehensive information on the full 224x224 ImageNet-1k. However,…
Human Guided Ground-truth Generation for Realistic Image Super-resolution
Du Chen, Jie Liang, Xindong Zhang +3
How to generate the ground-truth (GT) image is a critical issue for training realistic image super-resolution (Real-ISR) models. Existing methods mostly take a set of high-resoluti…
Spatial-Frequency Attention for Image Denoising
Shi Guo, Hongwei Yong, Xindong Zhang +2
The recently developed transformer networks have achieved impressive performance in image denoising by exploiting the self-attention (SA) in images. However, the existing methods m…
Efficient Long-Range Attention Network for Image Super-resolution
Xindong Zhang, Hui Zeng, Shi Guo +1
Recently, transformer-based methods have demonstrated impressive results in various vision tasks, including image super-resolution (SR), by exploiting the self-attention (SA) for f…
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Radu Timofte, Maurizio Denna +20
Image super-resolution is one of the most popular computer vision problems with many important applications to mobile devices. While many solutions have been proposed for this task…