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Recent advances in text-to-image (T2I) generation have enabled visually coherent image synthesis from descriptions, but generating images containing multiple given subjects remains challenging. As the number of reference identities…

Machine Learning · Computer Science 2026-04-10 Yucheng Zhou , Dubing Chen , Huan Zheng , Jianbing Shen

Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing complex scenes with multiple objects. While excelling in…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Hanan Gani , Shariq Farooq Bhat , Muzammal Naseer , Salman Khan , Peter Wonka

The recent innovations and breakthroughs in diffusion models have significantly expanded the possibilities of generating high-quality videos for the given prompts. Most existing works tackle the single-scene scenario with only one video…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Fuchen Long , Zhaofan Qiu , Ting Yao , Tao Mei

Despite the promising progress in subject-driven image generation, current models often deviate from the reference identities and struggle in complex scenes with multiple subjects. To address this challenge, we introduce OpenSubject, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Yexin Liu , Manyuan Zhang , Yueze Wang , Hongyu Li , Dian Zheng , Weiming Zhang , Changsheng Lu , Xunliang Cai , Yan Feng , Peng Pei , Harry Yang

Text-to-Video generation, which utilizes the provided text prompt to generate high-quality videos, has drawn increasing attention and achieved great success due to the development of diffusion models recently. Existing methods mainly rely…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zirui Pan , Xin Wang , Yipeng Zhang , Hong Chen , Kwan Man Cheng , Yaofei Wu , Wenwu Zhu

Recent advances in diffusion-based text-to-video (T2V) models have demonstrated remarkable progress, but these models still face challenges in generating videos with multiple objects. Most models struggle with accurately capturing complex…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Aimon Rahman , Jiang Liu , Ze Wang , Ximeng Sun , Jialian Wu , Xiaodong Yu , Yusheng Su , Vishal M. Patel , Zicheng Liu , Emad Barsoum

Interleaved image-text generation has emerged as a crucial multimodal task, aiming at creating sequences of interleaved visual and textual content given a query. Despite notable advancements in recent multimodal large language models…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Wei Chen , Lin Li , Yongqi Yang , Bin Wen , Fan Yang , Tingting Gao , Yu Wu , Long Chen

Customized text-to-video generation aims to generate high-quality videos guided by text prompts and subject references. Current approaches for personalizing text-to-video generation suffer from tackling multiple subjects, which is a more…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Zhao Wang , Aoxue Li , Lingting Zhu , Yong Guo , Qi Dou , Zhenguo Li

Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current foundational models predominantly focus on processing images,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhiyu Tan , Hao Yang , Luozheng Qin , Jia Gong , Mengping Yang , Hao Li

Multimodal Large Language Models (MLLMs) struggle with accurately capturing camera-object relations, especially for object orientation, camera viewpoint, and camera shots. This stems from the fact that existing MLLMs are trained on images…

Customized text-to-video generation aims to generate text-guided videos with user-given subjects, which has gained increasing attention. However, existing works are primarily limited to single-subject oriented text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Hong Chen , Xin Wang , Guanning Zeng , Yipeng Zhang , Yuwei Zhou , Feilin Han , Yaofei Wu , Wenwu Zhu

The continuous development of foundational models for video generation is evolving into various applications, with subject-consistent video generation still in the exploratory stage. We refer to this as Subject-to-Video, which extracts…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Lijie Liu , Tianxiang Ma , Bingchuan Li , Zhuowei Chen , Jiawei Liu , Gen Li , Siyu Zhou , Qian He , Xinglong Wu

In this paper, we introduce DirectorLLM, a novel video generation model that employs a large language model (LLM) to orchestrate human poses within videos. As foundational text-to-video models rapidly evolve, the demand for high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Kunpeng Song , Tingbo Hou , Zecheng He , Haoyu Ma , Jialiang Wang , Animesh Sinha , Sam Tsai , Yaqiao Luo , Xiaoliang Dai , Li Chen , Xide Xia , Peizhao Zhang , Peter Vajda , Ahmed Elgammal , Felix Juefei-Xu

Despite recent advances in video generation, existing models still lack fine-grained controllability, especially for multi-subject customization with consistent identity and interaction. In this paper, we propose PolyVivid, a multi-subject…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Teng Hu , Zhentao Yu , Zhengguang Zhou , Jiangning Zhang , Yuan Zhou , Qinglin Lu , Ran Yi

Customized text-to-video generation aims to produce high-quality videos that incorporate user-specified subject identities or motion patterns. However, existing methods mainly focus on personalizing a single concept, either subject identity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Chi-Pin Huang , Yen-Siang Wu , Hung-Kai Chung , Kai-Po Chang , Fu-En Yang , Yu-Chiang Frank Wang

Recent advancements in multimodal foundation models have yielded significant progress in vision-language understanding. Initial attempts have also explored the potential of multimodal large language models (MLLMs) for visual content…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Rongyao Fang , Chengqi Duan , Kun Wang , Hao Li , Hao Tian , Xingyu Zeng , Rui Zhao , Jifeng Dai , Hongsheng Li , Xihui Liu

Preference-conditioned image generation seeks to adapt generative models to individual users, producing outputs that reflect personal aesthetic choices beyond the given textual prompt. Despite recent progress, existing approaches either…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Wenyi Mo , Tianyu Zhang , Yalong Bai , Ligong Han , Ying Ba , Dimitris N. Metaxas

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

Diffusion Transformer has shown remarkable abilities in generating high-fidelity videos, delivering visually coherent frames and rich details over extended durations. However, existing video generation models still fall short in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Zhaoyang Li , Dongjun Qian , Kai Su , Qishuai Diao , Xiangyang Xia , Chang Liu , Wenfei Yang , Tianzhu Zhang , Zehuan Yuan

Multistep instructions, such as recipes and how-to guides, greatly benefit from visual aids, such as a series of images that accompany the instruction steps. While Large Language Models (LLMs) have become adept at generating coherent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 João Bordalo , Vasco Ramos , Rodrigo Valério , Diogo Glória-Silva , Yonatan Bitton , Michal Yarom , Idan Szpektor , Joao Magalhaes
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