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Vehicle-to-everything (V2X) technologies offer a promising paradigm to mitigate the limitations of constrained observability in single-vehicle systems. Prior work primarily focuses on single-frame cooperative perception, which fuses agents'…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Zewei Zhou , Hao Xiang , Zhaoliang Zheng , Seth Z. Zhao , Mingyue Lei , Yun Zhang , Tianhui Cai , Xinyi Liu , Johnson Liu , Maheswari Bajji , Xin Xia , Zhiyu Huang , Bolei Zhou , Jiaqi Ma

Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Lin Liu , Quande Liu , Shengju Qian , Yuan Zhou , Wengang Zhou , Houqiang Li , Lingxi Xie , Qi Tian

Large-scale video generation models have demonstrated high visual realism in diverse contexts, spurring interest in their potential as general-purpose world simulators. Existing benchmarks focus on individual subjects rather than scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Aaron Appelle , Jerome P. Lynch

The rapid progress in diffusion models, transformers, and language agents has unlocked new possibilities, yet their potential in user interfaces and commercial applications remains underexplored. We present Sketch-Search Agent, a novel…

Information Retrieval · Computer Science 2025-04-15 Edward Sun

Large text-to-image diffusion models have achieved remarkable success in generating diverse, high-quality images. Additionally, these models have been successfully leveraged to edit input images by just changing the text prompt. But when…

Computer Vision and Pattern Recognition · Computer Science 2023-08-11 Anant Khandelwal

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

Advanced diffusion-based Text-to-Image (T2I) models, such as the Stable Diffusion Model, have made significant progress in generating diverse and high-quality images using text prompts alone. However, when non-famous users require…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yang Li , Songlin Yang , Wei Wang , Jing Dong

Autonomous multimodal language models are rapidly evolving into web agents that can browse, click, and purchase items on behalf of users, posing a threat to display advertising designed for human eyes. Yet little is known about how these…

Information Retrieval · Computer Science 2025-11-13 Joel Nitu , Heidrun Mühle , Andreas Stöckl

Digital storytelling, essential in entertainment, education, and marketing, faces challenges in production scalability and flexibility. The StoryAgent framework, introduced in this paper, utilizes Large Language Models and generative tools…

Computation and Language · Computer Science 2024-06-24 Samuel S. Sohn , Danrui Li , Sen Zhang , Che-Jui Chang , Mubbasir Kapadia

The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users. The intended generation can be expressed in natural language, with the model producing faithful…

The increasing use of synthetic media, particularly deepfakes, is an emerging challenge for digital content verification. Although recent studies use both audio and visual information, most integrate these cues within a single model, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Sayeem Been Zaman , Wasimul Karim , Arefin Ittesafun Abian , Reem E. Mohamed , Md Rafiqul Islam , Asif Karim , Sami Azam

Generative diffusion models are developing rapidly and attracting increasing attention due to their wide range of applications. Image-to-Video (I2V) generation has become a major focus in the field of video synthesis. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Ailing Zhang , Lina Lei , Dehong Kong , Zhixin Wang , Jiaqi Xu , Fenglong Song , Chun-Le Guo , Chang Liu , Fan Li , Jie Chen

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

Bundle generation aims to provide a bundle of items for the user, and has been widely studied and applied on online service platforms. Existing bundle generation methods mainly utilized user's preference from historical interactions in…

Information Retrieval · Computer Science 2023-10-30 Shixuan Zhu , Chuan Cui , JunTong Hu , Qi Shen , Yu Ji , Zhihua Wei

The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent videos from natural language descriptions. Despite these achievements, their vulnerability to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Changzhen Li , Yuecong Min , Jie Zhang , Zheng Yuan , Shiguang Shan , Xilin Chen

Assessing advertisements, specifically on the basis of user preferences and ad quality, is crucial to the marketing industry. Although recent studies have attempted to use deep neural networks for this purpose, these studies have not…

Computer Vision and Pattern Recognition · Computer Science 2021-02-10 Kyung-Wha Park , Jung-Woo Ha , JungHoon Lee , Sunyoung Kwon , Kyung-Min Kim , Byoung-Tak Zhang

User prompts for generative AI models are often underspecified, leading to a misalignment between the user intent and models' understanding. As a result, users commonly have to painstakingly refine their prompts. We study this alignment…

Artificial Intelligence · Computer Science 2025-10-27 Meera Hahn , Wenjun Zeng , Nithish Kannen , Rich Galt , Kartikeya Badola , Been Kim , Zi Wang

As artificial intelligence-generated content (AIGC) continues to evolve, video-to-audio (V2A) generation has emerged as a key area with promising applications in multimedia editing, augmented reality, and automated content creation. While…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Yuhuan You , Xihong Wu , Tianshu Qu

Vision-language models have been key to the development of open-vocabulary 2D semantic segmentation. Lifting these models from 2D images to 3D scenes, however, remains a challenging problem. Existing approaches typically back-project and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Tomas Berriel Martins , Martin R. Oswald , Javier Civera

Text-to-video retrieval enables users to find relevant video content using natural language queries, a task that has grown increasingly important with the rapid expansion of online video. Over the past six years, research has produced…