23 citations · 143 across the 50 of their papers we have counts for
9 papers · 1 filter
Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers
Yunshan Zhong, Yuyao Zhou, Yuxin Zhang +5
Data-free quantization (DFQ) enables model quantization without accessing real data, addressing concerns regarding data security and privacy. With the growing adoption of Vision Tr…
TextDestroyer: A Training- and Annotation-Free Diffusion Method for Destroying Anomal Text from Images
Mengcheng Li, Fei Chao
In this paper, we propose TextDestroyer, the first training- and annotation-free method for scene text destruction using a pre-trained diffusion model. Existing scene text removal…
Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing
Pengfei Jiang, Mingbao Lin, Fei Chao
Current methods commonly utilize three-branch structures of inversion, reconstruction, and editing, to tackle consistent image editing task. However, these methods lack control ove…
ConCLVD: Controllable Chinese Landscape Video Generation via Diffusion Model
Dingming Liu, Shaowei Li, Ruoyan Zhou +4
Chinese landscape painting is a gem of Chinese cultural and artistic heritage that showcases the splendor of nature through the deep observations and imaginations of its painters.…
Rethinking 3D Dense Caption and Visual Grounding in A Unified Framework through Prompt-based Localization
Yongdong Luo, Haojia Lin, Xiawu Zheng +6
3D Visual Grounding (3DVG) and 3D Dense Captioning (3DDC) are two crucial tasks in various 3D applications, which require both shared and complementary information in localization…
AffineQuant: Affine Transformation Quantization for Large Language Models
Yuexiao Ma, Huixia Li, Xiawu Zheng +6
The significant resource requirements associated with Large-scale Language Models (LLMs) have generated considerable interest in the development of techniques aimed at compressing…
EBFT: Effective and Block-Wise Fine-Tuning for Sparse LLMs
Song Guo, Fan Wu, Lei Zhang +5
Existing methods for fine-tuning sparse LLMs often suffer from resource-intensive requirements and high retraining costs. Additionally, many fine-tuning methods often rely on appro…
Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration
Yimin Xu, Nanxi Gao, Zhongyun Shan +2
In contrast to traditional image restoration methods, all-in-one image restoration techniques are gaining increased attention for their ability to restore images affected by divers…
Learning Image Demoireing from Unpaired Real Data
Yunshan Zhong, Yuyao Zhou, Yuxin Zhang +2
This paper focuses on addressing the issue of image demoireing. Unlike the large volume of existing studies that rely on learning from paired real data, we attempt to learn a demoi…