383 citations · 1.2k across the 28 of their papers we have counts for
8 papers · 1 filter
Pretrained Diffusion Models for Unified Human Motion Synthesis
Jianxin Ma, Shuai Bai, Chang Zhou
Generative modeling of human motion has broad applications in computer animation, virtual reality, and robotics. Conventional approaches develop separate models for different motio…
Single Stage Virtual Try-on via Deformable Attention Flows
Shuai Bai, Huiling Zhou, Zhikang Li +2
Virtual try-on aims to generate a photo-realistic fitting result given an in-shop garment and a reference person image. Existing methods usually build up multi-stage frameworks to…
M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing
Zhikang Li, Huiling Zhou, Shuai Bai +3
The fashion industry has diverse applications in multi-modal image generation and editing. It aims to create a desired high-fidelity image with the multi-modal conditional signal a…
In-N-Out Generative Learning for Dense Unsupervised Video Segmentation
Xiao Pan, Peike Li, Zongxin Yang +5
In this paper, we focus on unsupervised learning for Video Object Segmentation (VOS) which learns visual correspondence (i.e., the similarity between pixel-level features) from unl…
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Peng Wang, An Yang, Rui Men +7
In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization. We propose OFA, a Task-Agnostic and Mo…
Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
Shuai Bai, Zhedong Zheng, Xiaohan Wang +5
Vehicle search is one basic task for the efficient traffic management in terms of the AI City. Most existing practices focus on the image-based vehicle matching, including vehicle…
M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers
Zhu Zhang, Jianxin Ma, Chang Zhou +6
Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as…
CogView: Mastering Text-to-Image Generation via Transformers
Ming Ding, Zhuoyi Yang, Wenyi Hong +8
Text-to-Image generation in the general domain has long been an open problem, which requires both a powerful generative model and cross-modal understanding. We propose CogView, a 4…