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Recent advances in image editing, driven by image diffusion models, have shown remarkable progress. However, significant challenges remain, as these models often struggle to follow complex edit instructions accurately and frequently…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Noam Rotstein , Gal Yona , Daniel Silver , Roy Velich , David Bensaïd , Ron Kimmel

Text-driven image manipulation remains challenging in training or inference flexibility. Conditional generative models depend heavily on expensive annotated training data. Meanwhile, recent frameworks, which leverage pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Yueming Lyu , Tianwei Lin , Fu Li , Dongliang He , Jing Dong , Tieniu Tan

In this paper, we are interested in editing text in natural images, which aims to replace or modify a word in the source image with another one while maintaining its realistic look. This task is challenging, as the styles of both background…

Computer Vision and Pattern Recognition · Computer Science 2019-08-09 Liang Wu , Chengquan Zhang , Jiaming Liu , Junyu Han , Jingtuo Liu , Errui Ding , Xiang Bai

We present a novel approach to data-to-text generation based on iterative text editing. Our approach maximizes the completeness and semantic accuracy of the output text while leveraging the abilities of recent pre-trained models for text…

Computation and Language · Computer Science 2021-01-29 Zdeněk Kasner , Ondřej Dušek

We propose a method for adding sound-guided visual effects to specific regions of videos with a zero-shot setting. Animating the appearance of the visual effect is challenging because each frame of the edited video should have visual…

Computer Vision and Pattern Recognition · Computer Science 2023-04-17 Seung Hyun Lee , Sieun Kim , Innfarn Yoo , Feng Yang , Donghyeon Cho , Youngseo Kim , Huiwen Chang , Jinkyu Kim , Sangpil Kim

Recently, language-guided global image editing draws increasing attention with growing application potentials. However, previous GAN-based methods are not only confined to domain-specific, low-resolution data but also lacking in…

Computer Vision and Pattern Recognition · Computer Science 2021-06-25 Jing Shi , Ning Xu , Yihang Xu , Trung Bui , Franck Dernoncourt , Chenliang Xu

Recent text-to-video diffusion models have achieved impressive progress. In practice, users often desire the ability to control object motion and camera movement independently for customized video creation. However, current methods lack the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Shiyuan Yang , Liang Hou , Haibin Huang , Chongyang Ma , Pengfei Wan , Di Zhang , Xiaodong Chen , Jing Liao

Recent advances in diffusion models have enabled high-quality generation and manipulation of images guided by texts, as well as concept learning from images. However, naive applications of existing methods to editing tasks that require…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xudong Liu , Zikun Chen , Ruowei Jiang , Ziyi Wu , Kejia Yin , Han Zhao , Parham Aarabi , Igor Gilitschenski

Recently, diffusion-based generative models have achieved remarkable success for image generation and edition. However, existing diffusion-based video editing approaches lack the ability to offer precise control over generated content that…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Paul Couairon , Clément Rambour , Jean-Emmanuel Haugeard , Nicolas Thome

Generating human portraits is a hot topic in the image generation area, e.g. mask-to-face generation and text-to-face generation. However, these unimodal generation methods lack controllability in image generation. Controllability can be…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Debin Meng , Christos Tzelepis , Ioannis Patras , Georgios Tzimiropoulos

Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/objects or their layout in a fine-grained fashion. Previous…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Omri Avrahami , Thomas Hayes , Oran Gafni , Sonal Gupta , Yaniv Taigman , Devi Parikh , Dani Lischinski , Ohad Fried , Xi Yin

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. %…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Nikita Starodubcev , Dmitry Baranchuk , Valentin Khrulkov , Artem Babenko

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

Generating high-quality and diverse human images is an important yet challenging task in vision and graphics. However, existing generative models often fall short under the high diversity of clothing shapes and textures. Furthermore, the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-01 Yuming Jiang , Shuai Yang , Haonan Qiu , Wayne Wu , Chen Change Loy , Ziwei Liu

We introduce a new method to efficiently create text-to-image models from a pre-trained CLIP and StyleGAN. It enables text driven sampling with an existing generative model without any external data or fine-tuning. This is achieved by…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Justin N. M. Pinkney , Chuan Li

Large-scale text-to-video (T2V) diffusion models have great progress in recent years in terms of visual quality, motion and temporal consistency. However, the generation process is still a black box, where all attributes (e.g., appearance,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jiwen Yu , Xiaodong Cun , Chenyang Qi , Yong Zhang , Xintao Wang , Ying Shan , Jian Zhang

We address the challenge of building task-agnostic classifiers using only text descriptions, demonstrating a unified approach to image classification, 3D point cloud classification, and action recognition from scenes. Unlike approaches that…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Ohad Amosy , Tomer Volk , Eilam Shapira , Eyal Ben-David , Roi Reichart , Gal Chechik

We propose a method for scene-level sketch-to-photo synthesis with text guidance. Although object-level sketch-to-photo synthesis has been widely studied, whole-scene synthesis is still challenging without reference photos that adequately…

Computer Vision and Pattern Recognition · Computer Science 2023-02-15 AprilPyone MaungMaung , Makoto Shing , Kentaro Mitsui , Kei Sawada , Fumio Okura

Generating semantically coherent and visually accurate talking faces requires bridging the gap between linguistic meaning and facial articulation. Although audio-driven methods remain prevalent, their reliance on high-quality paired audio…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Xu Wang , Shengeng Tang , Fei Wang , Lechao Cheng , Dan Guo , Feng Xue , Richang Hong

Diffusion-based image editing is a composite process of preserving the source image content and generating new content or applying modifications. While current editing approaches have made improvements under text guidance, most of them have…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Tianrui Huang , Pu Cao , Lu Yang , Chun Liu , Mengjie Hu , Zhiwei Liu , Qing Song
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