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Recent advancements in generative models have revolutionized the field of artificial intelligence, enabling the creation of highly-realistic and detailed images. In this study, we propose a novel Mask Conditional Text-to-Image Generative…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Rami Skaik , Leonardo Rossi , Tomaso Fontanini , Andrea Prati

Large diffusion-based Text-to-Image (T2I) models have shown impressive generative powers for text-to-image generation as well as spatially conditioned image generation. For most applications, we can train the model end-toend with paired…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Nithin Gopalakrishnan Nair , Jeya Maria Jose Valanarasu , Vishal M Patel

We present TokenCompose, a Latent Diffusion Model for text-to-image generation that achieves enhanced consistency between user-specified text prompts and model-generated images. Despite its tremendous success, the standard denoising process…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zirui Wang , Zhizhou Sha , Zheng Ding , Yilin Wang , Zhuowen Tu

Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose RealCompo, a new…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Xinchen Zhang , Ling Yang , Yaqi Cai , Zhaochen Yu , Kai-Ni Wang , Jiake Xie , Ye Tian , Minkai Xu , Yong Tang , Yujiu Yang , Bin Cui

Recently, perceptual image compression has achieved significant advancements, delivering high visual quality at low bitrates for natural images. However, for screen content, existing methods often produce noticeable artifacts when…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Tongda Xu , Jiahao Li , Bin Li , Yan Wang , Ya-Qin Zhang , Yan Lu

This paper introduces MIDI, a novel paradigm for compositional 3D scene generation from a single image. Unlike existing methods that rely on reconstruction or retrieval techniques or recent approaches that employ multi-stage…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Zehuan Huang , Yuan-Chen Guo , Xingqiao An , Yunhan Yang , Yangguang Li , Zi-Xin Zou , Ding Liang , Xihui Liu , Yan-Pei Cao , Lu Sheng

Long-horizon contact-rich manipulation has long been a challenging problem, as it requires reasoning over both discrete contact modes and continuous object motion. We introduce Implicit Contact Diffuser (ICD), a diffusion-based model that…

Robotics · Computer Science 2024-10-23 Zixuan Huang , Yinong He , Yating Lin , Dmitry Berenson

There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the insufficient modeling of multiple objects and their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Yunnan Wang , Ziqiang Li , Zequn Zhang , Wenyao Zhang , Baao Xie , Xihui Liu , Wenjun Zeng , Xin Jin

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Compositional diffusion planning generates long-horizon trajectories by stitching together overlapping short-horizon segments through score composition. However, when local plan distributions are multimodal, existing compositional methods…

Robotics · Computer Science 2026-05-06 Kyowoon Lee , Yunhao Luo , Anh Tong , Jaesik Choi

Recent advancements in text-to-image models, particularly diffusion models, have shown significant promise. However, compositional text-to-image models frequently encounter difficulties in generating high-quality images that accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Song Wen , Guian Fang , Renrui Zhang , Peng Gao , Hao Dong , Dimitris Metaxas

Diffusion models have shown promise in text generation, but often struggle with generating long, coherent, and contextually accurate text. Token-level diffusion doesn't model word-order dependencies explicitly and operates on short, fixed…

Computation and Language · Computer Science 2025-05-27 Xiaochen Zhu , Georgi Karadzhov , Chenxi Whitehouse , Andreas Vlachos

Text-to-image diffusion models have shown impressive capabilities in generating realistic visuals from natural-language prompts, yet they often struggle with accurately binding attributes to corresponding objects, especially in prompts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Do Huu Dat , Nam Hyeonu , Po-Yuan Mao , Tae-Hyun Oh

Recent advances in diffusion models have demonstrated impressive capability in generating high-quality images for simple prompts. However, when confronted with complex prompts involving multiple objects and hierarchical structures, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Hongji Yang , Yucheng Zhou , Wencheng Han , Runzhou Tao , Zhongying Qiu , Jianfei Yang , Jianbing Shen

Text-driven person image generation is an emerging and challenging task in cross-modality image generation. Controllable person image generation promotes a wide range of applications such as digital human interaction and virtual try-on.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-14 Kaiduo Zhang , Muyi Sun , Jianxin Sun , Binghao Zhao , Kunbo Zhang , Zhenan Sun , Tieniu Tan

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

Large text-guided diffusion models, such as DALLE-2, are able to generate stunning photorealistic images given natural language descriptions. While such models are highly flexible, they struggle to understand the composition of certain…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Nan Liu , Shuang Li , Yilun Du , Antonio Torralba , Joshua B. Tenenbaum

Existing text-to-image models struggle to follow complex text prompts, raising the need for extra grounding inputs for better controllability. In this work, we propose to decompose a scene into visual primitives - denoted as dense blob…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Weili Nie , Sifei Liu , Morteza Mardani , Chao Liu , Benjamin Eckart , Arash Vahdat

Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provide object-wise manipulation capability. To support wider…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Runhui Huang , Kaixin Cai , Jianhua Han , Xiaodan Liang , Renjing Pei , Guansong Lu , Songcen Xu , Wei Zhang , Hang Xu