Publications (8)
Neural Texture Extraction and Distribution for Controllable Person Image Synthesis
Yurui Ren, Xiaoqing Fan, Ge Li +2
We deal with the controllable person image synthesis task which aims to re-render a human from a reference image with explicit control over body pose and appearance. Observing that…
Combining Attention with Flow for Person Image Synthesis
Yurui Ren, Yubo Wu, Thomas H. Li +2
Pose-guided person image synthesis aims to synthesize person images by transforming reference images into target poses. In this paper, we observe that the commonly used spatial tra…
Deep Image Spatial Transformation for Person Image Generation
Yurui Ren, Xiaoming Yu, Junming Chen +2
Pose-guided person image generation is to transform a source person image to a target pose. This task requires spatial manipulations of source data. However, Convolutional Neural N…
Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation
Yurui Ren, Ge Li, Shan Liu +1
Pose-guided person image generation and animation aim to transform a source person image to target poses. These tasks require spatial manipulation of source data. However, Convolut…
StructureFlow: Image Inpainting via Structure-aware Appearance Flow
Yurui Ren, Xiaoming Yu, Ruonan Zhang +3
Image inpainting techniques have shown significant improvements by using deep neural networks recently. However, most of them may either fail to reconstruct reasonable structures o…
Deep Geometry Post-Processing for Decompressed Point Clouds
Xiaoqing Fan, Ge Li, Dingquan Li +3
Point cloud compression plays a crucial role in reducing the huge cost of data storage and transmission. However, distortions can be introduced into the decompressed point clouds d…
PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering
Yurui Ren, Ge Li, Yuanqi Chen +2
Generating portrait images by controlling the motions of existing faces is an important task of great consequence to social media industries. For easy use and intuitive control, se…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…