17 citations · 18 across the 7 of their papers we have counts for
9 papers
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…
Describe, Don't Dictate: Semantic Image Editing with Natural Language Intent
En Ci, Shanyan Guan, Yanhao Ge +5
Despite the progress in text-to-image generation, semantic image editing remains a challenge. Inversion-based algorithms unavoidably introduce reconstruction errors, while instruct…
EasySplat: View-Adaptive Learning makes 3D Gaussian Splatting Easy
Ao Gao, Luosong Guo, Tao Chen +4
3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of…
STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution
Rui Xie, Yinhong Liu, Penghao Zhou +7
Image diffusion models have been adapted for real-world video super-resolution to tackle over-smoothing issues in GAN-based methods. However, these models struggle to maintain temp…
Learning to Decouple the Lights for 3D Face Texture Modeling
Tianxin Huang, Zhenyu Zhang, Ying Tai +1
Existing research has made impressive strides in reconstructing human facial shapes and textures from images with well-illuminated faces and minimal external occlusions. Neverthele…
StrandHead: Text to Hair-Disentangled 3D Head Avatars Using Human-Centric Priors
Xiaokun Sun, Zeyu Cai, Ying Tai +2
While haircut indicates distinct personality, existing avatar generation methods fail to model practical hair due to the data limitation or entangled representation. We propose Str…
Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability
Xuelin Qian, Yu Wang, Simian Luo +9
Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…
Deepfake Generation and Detection: A Benchmark and Survey
Gan Pei, Jiangning Zhang, Menghan Hu +6
Deepfake is a technology dedicated to creating highly realistic facial images and videos under specific conditions, which has significant application potential in fields such as en…
Learning Versatile 3D Shape Generation with Improved AR Models
Simian Luo, Xuelin Qian, Yanwei Fu +5
Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space. While this approach has been extended to the…