11 papers
SynVAR: Synergizing Spatial and Semantic Alignment in Visual Autoregressive Model
Zhennan Chen, Tianxing Shi, Pengcheng Xu +5
VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling complex scenes with multiple obj…
Spiking Pyramid Wavelet Transformation for High-efficient and Low-energy Image Restoration
Chen Zhao, Xiantao Hu, Song Wu +5
Spiking neural networks (SNNs) have garnered significant interest in computer vision due to their potential for efficiency and biological inspiration. While spiking CNN-based metho…
VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset
Zhizhou Chen, Shanyan Guan, Zhanxin Gao +6
Directly editing ultra-high-resolution (UHR) images is valuable but underexplored, primarily due to the lack of high-quality data and the challenge in modeling high-frequency textu…
TripVVT: A Large-Scale Triplet Dataset and a Coarse-Mask Baseline for In-the-Wild Video Virtual Try-On
Dingbao Shao, Song Wu, Shenyi Wang +9
Due to the scarcity of large-scale in-the-wild triplet data and the improper use of masks, the performance of video virtual try-on models remains limited. In this paper, we first i…
From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmark
Chen Zhao, Yunzhe Xu, Zhizhou Chen +5
Ultra-high-definition (UHD) image restoration poses unique challenges due to the high spatial resolution, diverse content, and fine-grained structures present in UHD images. To add…
DiP: Taming Diffusion Models in Pixel Space
Zhennan Chen, Junwei Zhu, Xu Chen +6
Diffusion models face a fundamental trade-off between generation quality and computational efficiency. Latent Diffusion Models (LDMs) offer an efficient solution but suffer from po…