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Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind. If this new technology is to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Marek Kowalski , Stephan J. Garbin , Virginia Estellers , Tadas Baltrušaitis , Matthew Johnson , Jamie Shotton

Image description task has been invariably examined in a static manner with qualitative presumptions held to be universally applicable, regardless of the scope or target of the description. In practice, however, different viewers may pay…

Computation and Language · Computer Science 2018-05-02 Andrew Shin , Yoshitaka Ushiku , Tatsuya Harada

Recent approaches have achieved great success in image generation from structured inputs, e.g., semantic segmentation, scene graph or layout. Although these methods allow specification of objects and their locations at image-level, they…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Ke Ma , Bo Zhao , Leonid Sigal

The text-to-image (T2I) personalization diffusion model can generate images of the novel concept based on the user input text caption. However, existing T2I personalized methods either require test-time fine-tuning or fail to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Xiao Guo , Manh Tran , Jiaxin Cheng , Xiaoming Liu

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centric images, an intractable problem is how to preserve the face identity for conditioned face images. Existing methods either require…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Zhuowei Chen , Shancheng Fang , Wei Liu , Qian He , Mengqi Huang , Yongdong Zhang , Zhendong Mao

Multi-ID customization is an interesting topic in computer vision and attracts considerable attention recently. Given the ID images of multiple individuals, its purpose is to generate a customized image that seamlessly integrates them while…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Jiawei Lin , Guanlong Jiao , Jianjin Xu

Accurately labeled real-world training data can be scarce, and hence recent works adapt, modify or generate images to boost target datasets. However, retaining relevant details from input data in the generated images is challenging and…

Computer Vision and Pattern Recognition · Computer Science 2019-11-11 Marcel Bühler , Seonwook Park , Shalini De Mello , Xucong Zhang , Otmar Hilliges

Enabling image generation models to be spatially controlled is an important area of research, empowering users to better generate images according to their own fine-grained specifications via e.g. edge maps, poses. Although this task has…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Guoxuan Xia , Harleen Hanspal , Petru-Daniel Tudosiu , Shifeng Zhang , Sarah Parisot

Personalized image generation via text prompts has great potential to improve daily life and professional work by facilitating the creation of customized visual content. The aim of image personalization is to create images based on a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Mingxiao Li , Tingyu Qu , Tinne Tuytelaars , Marie-Francine Moens

Personalized image generation aims to integrate user-provided concepts into text-to-image models, enabling the generation of customized content based on a given prompt. Recent zero-shot approaches, particularly those leveraging diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Yiheng Lin , Shifang Zhao , Ting Liu , Xiaochao Qu , Luoqi Liu , Yao Zhao , Yunchao Wei

In recent years, Generative Adversarial Networks (GANs) have improved steadily towards generating increasingly impressive real-world images. It is useful to steer the image generation process for purposes such as content creation. This can…

Computer Vision and Pattern Recognition · Computer Science 2020-05-12 David Stap , Maurits Bleeker , Sarah Ibrahimi , Maartje ter Hoeve

Listening head generation aims to synthesize a non-verbal responsive listener head by modeling the correlation between the speaker and the listener in dynamic conversion.The applications of listener agent generation in virtual interaction…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Xi Liu , Ying Guo , Cheng Zhen , Tong Li , Yingying Ao , Pengfei Yan

Recent remarkable advances in large-scale text-to-image diffusion models have inspired a significant breakthrough in text-to-3D generation, pursuing 3D content creation solely from a given text prompt. However, existing text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Yang Chen , Yingwei Pan , Yehao Li , Ting Yao , Tao Mei

This paper studies the task of full generative modelling of realistic images of humans, guided only by coarse sketch of the pose, while providing control over the specific instance or type of outfit worn by the user. This is a difficult…

Computer Vision and Pattern Recognition · Computer Science 2019-06-06 Xu Chen , Jie Song , Otmar Hilliges

Existing image-to-image transformation approaches primarily focus on synthesizing visually pleasing data. Generating images with correct identity labels is challenging yet much less explored. It is even more challenging to deal with image…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Wei Xiong , Yutong He , Yixuan Zhang , Wenhan Luo , Lin Ma , Jiebo Luo

Collecting and labeling training data is one important step for learning-based methods because the process is time-consuming and biased. For face analysis tasks, although some generative models can be used to generate face data, they can…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Dingyun Zhang , Chenglai Zhong , Yudong Guo , Yang Hong , Juyong Zhang

Image generation has raised tremendous attention in both academic and industrial areas, especially for the conditional and target-oriented image generation, such as criminal portrait and fashion design. Although the current studies have…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Songyao Jiang , Hongfu Liu , Yue Wu , Yun Fu

While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Previous methods rely on pre-estimated structural information…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Hang Zhou , Yasheng Sun , Wayne Wu , Chen Change Loy , Xiaogang Wang , Ziwei Liu

Identity-consistent generation has become an important focus in text-to-image research, with recent models achieving notable success in producing images aligned with a reference identity. Yet, the scarcity of large-scale paired datasets…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Hengyuan Xu , Wei Cheng , Peng Xing , Yixiao Fang , Shuhan Wu , Rui Wang , Xianfang Zeng , Daxin Jiang , Gang Yu , Xingjun Ma , Yu-Gang Jiang