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Recently, parallel text generation has received widespread attention due to its success in generation efficiency. Although many advanced techniques are proposed to improve its generation quality, they still need the help of an…

Computation and Language · Computer Science 2022-04-06 Yu Bao , Hao Zhou , Shujian Huang , Dongqi Wang , Lihua Qian , Xinyu Dai , Jiajun Chen , Lei Li

Latent diffusion models (LDMs) dominate high-quality image generation, yet integrating representation learning with generative modeling remains a challenge. We introduce a novel generative image modeling framework that seamlessly bridges…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Theodoros Kouzelis , Efstathios Karypidis , Ioannis Kakogeorgiou , Spyros Gidaris , Nikos Komodakis

Diffusion probabilistic models have achieved enormous success in the field of image generation and manipulation. In this paper, we explore a novel paradigm of using the diffusion model and classifier guidance in the latent semantic space…

Computer Vision and Pattern Recognition · Computer Science 2023-05-25 Changhao Shi , Haomiao Ni , Kai Li , Shaobo Han , Mingfu Liang , Martin Renqiang Min

Significant advances have been made in human-centric video generation, yet the joint video-depth generation problem remains underexplored. Most existing monocular depth estimation methods may not generalize well to synthesized images or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Yuanhao Zhai , Kevin Lin , Linjie Li , Chung-Ching Lin , Jianfeng Wang , Zhengyuan Yang , David Doermann , Junsong Yuan , Zicheng Liu , Lijuan Wang

Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the existing approaches mainly focus on generating motions with…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Yiming Wu , Wei Ji , Kecheng Zheng , Zicheng Wang , Dong Xu

Language-guided image generation has achieved great success nowadays by using diffusion models. However, texts can be less detailed to describe highly-specific subjects such as a particular dog or a certain car, which makes pure…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Yiyang Ma , Huan Yang , Wenjing Wang , Jianlong Fu , Jiaying Liu

In various natural language processing (NLP) tasks, fine-tuning Pre-trained Language Models (PLMs) often leads to the issue of spurious correlations, which negatively impacts performance, particularly when dealing with out-of-distribution…

Computation and Language · Computer Science 2025-04-17 Suyoung Bae , Hyojun Kim , YunSeok Choi , Jee-Hyong Lee

Text-conditioned motion synthesis has made remarkable progress with the emergence of diffusion models. However, the majority of these motion diffusion models are primarily designed for a single character and overlook multi-human…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Zhenzhi Wang , Jingbo Wang , Yixuan Li , Dahua Lin , Bo Dai

Animation of 2D hand-drawn sketches provides an effective medium for visual communication. However, these sketches pose challenges, particularly in handling occlusions and accurately mapping motion. While 3D animation naturally addresses…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Gaurav Rai , Ojaswa Sharma

Diffusion-based image translation guided by semantic texts or a single target image has enabled flexible style transfer which is not limited to the specific domains. Unfortunately, due to the stochastic nature of diffusion models, it is…

Computer Vision and Pattern Recognition · Computer Science 2023-02-02 Gihyun Kwon , Jong Chul Ye

Vision-Language-Action (VLA) models have achieved remarkable progress in robotic manipulation by mapping multimodal observations and instructions directly to actions. However, they typically mimic expert trajectories without predictive…

Probabilistic human motion prediction aims to forecast multiple possible future movements from past observations. While current approaches report high diversity and realism, they often generate motions with undetected limb stretching and…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Cecilia Curreli , Dominik Muhle , Abhishek Saroha , Zhenzhang Ye , Riccardo Marin , Daniel Cremers

Recent years have witnessed the success of diffusion models in image customization tasks. However, existing mask-guided human erasing methods still struggle in complex scenarios such as human-human occlusion, human-object entanglement, and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Jinghan Yu , Junhao Xiao , Zhiyuan Ma , Yue Ma , Kaiqi Liu , Yuhan Wang , Daizong Liu , Xianghao Meng , Jianjun Li

Generating sewing patterns in garment design is receiving increasing attention due to its CG-friendly and flexible-editing nature. Previous sewing pattern generation methods have been able to produce exquisite clothing, but struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Shengqi Liu , Yuhao Cheng , Zhuo Chen , Xingyu Ren , Wenhan Zhu , Lincheng Li , Mengxiao Bi , Xiaokang Yang , Yichao Yan

Recent advances in high-fidelity semantic image editing heavily rely on the presumably disentangled latent spaces of the state-of-the-art generative models, such as StyleGAN. Specifically, recent works show that it is possible to achieve…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Valentin Khrulkov , Leyla Mirvakhabova , Ivan Oseledets , Artem Babenko

Text-conditioned human motion generation, which allows for user interaction through natural language, has become increasingly popular. Existing methods typically generate short, isolated motions based on a single input sentence. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Kaifeng Zhao , Gen Li , Siyu Tang

Generating motion for arbitrary skeletons is a longstanding challenge in computer graphics, remaining largely unexplored due to the scarcity of diverse datasets and the irregular nature of the data. In this work, we introduce AnyTop, a…

Graphics · Computer Science 2025-06-06 Inbar Gat , Sigal Raab , Guy Tevet , Yuval Reshef , Amit H. Bermano , Daniel Cohen-Or

Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models pre-trained on large-scale image-text pairs are highly…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Wenliang Zhao , Yongming Rao , Zuyan Liu , Benlin Liu , Jie Zhou , Jiwen Lu

The generation of 3D clothed humans has attracted increasing attention in recent years. However, existing work cannot generate layered high-quality 3D humans with consistent body structures. As a result, these methods are unable to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yi Wang , Jian Ma , Ruizhi Shao , Qiao Feng , Yu-Kun Lai , Yebin Liu , Kun Li

Recent advances in image editing leverage latent diffusion models (LDMs) for versatile, text-prompt-driven edits across diverse tasks. Yet, maintaining pixel-level edge structures-crucial for tasks such as photorealistic style transfer or…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Minsu Gong , Nuri Ryu , Jungseul Ok , Sunghyun Cho