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In the light of exponentially increasing video content, video summarization has attracted a lot of attention recently due to its ability to optimize time and storage. Characteristics of a good summary of a video depend on the particular…

Computer Vision and Pattern Recognition · Computer Science 2018-12-31 Vishal Kaushal , Sandeep Subramanian , Suraj Kothawade , Rishabh Iyer , Ganesh Ramakrishnan

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing consistent 3D scenes from these outputs remains challenging, due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yisu Zhang , Chenjie Cao , Tengfei Wang , Xuhui Zuo , Junta Wu , Jianke Zhu , Chunchao Guo

In AI-facilitated teaching, leveraging various query styles to interpret abstract text descriptions is crucial for ensuring high-quality teaching. However, current retrieval models primarily focus on natural text-image retrieval, making…

Information Retrieval · Computer Science 2025-05-21 Yanhao Jia , Xinyi Wu , Hao Li , Qinglin Zhang , Yuxiao Hu , Shuai Zhao , Wenqi Fan

High-quality driving video generation is crucial for providing training data for autonomous driving models. However, current generative models rarely focus on enhancing camera motion control under multi-view tasks, which is essential for…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Yining Yao , Xi Guo , Chenjing Ding , Wei Wu

We propose a multiple instance learning approach to content-based retrieval of classroom video for the purpose of supporting human assessing the learning environment. The key element of our approach is a mapping between the semantic…

Information Retrieval · Computer Science 2014-03-26 Qifeng Qiao , Peter A. Beling

The generation of temporally consistent, high-fidelity driving videos over extended horizons presents a fundamental challenge in autonomous driving world modeling. Existing approaches often suffer from error accumulation and feature…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiamin Wang , Yichen Yao , Xiang Feng , Hang Wu , Yaming Wang , Qingqiu Huang , Yuexin Ma , Xinge Zhu

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The first category needs…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Xiao Wang , Shiao Wang , Chuanming Tang , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

We introduce a framework that enables both multi-view character consistency and 3D camera control in video diffusion models through a novel customization data pipeline. We train the character consistency component with recorded volumetric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Yuancheng Xu , Wenqi Xian , Li Ma , Julien Philip , Ahmet Levent Taşel , Yiwei Zhao , Ryan Burgert , Mingming He , Oliver Hermann , Oliver Pilarski , Rahul Garg , Paul Debevec , Ning Yu

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

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject. Existing methods try to tackle this challenge and generate…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Jiahao Wang , Caixia Yan , Haonan Lin , Weizhan Zhang , Mengmeng Wang , Tieliang Gong , Guang Dai , Hao Sun

Current motion-conditioned video generation methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction. We present MotionStream, enabling sub-second latency with up to 29 FPS…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Joonghyuk Shin , Zhengqi Li , Richard Zhang , Jun-Yan Zhu , Jaesik Park , Eli Shechtman , Xun Huang

Recent advances in multi-modal generative models have driven substantial improvements in image editing. However, current generative models still struggle with handling diverse and complex image editing tasks that require implicit reasoning,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Feng Han , Yibin Wang , Chenglin Li , Zheming Liang , Dianyi Wang , Yang Jiao , Zhipeng Wei , Chao Gong , Cheng Jin , Jingjing Chen , Jiaqi Wang

Visual storytelling with diffusion models has made impressive strides in maintaining character consistency across narrative scenes. However, a critical gap remains: while these methods ensure a character remains consistent across scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Manogna Sreenivas , Rohit Kumar , Soma Biswas

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng

Real-world video creation often involves a complex reasoning workflow of selecting relevant shots from noisy materials, planning missing shots for narrative completeness, and organizing them into coherent storylines. However, existing…

Multimedia · Computer Science 2026-04-20 Huanran Hu , Zihui Ren , Dingyi Yang , Liangyu Chen , Qixiang Gao , Tiezheng Ge , Qin Jin

Despite impressive progress in video generation, existing models remain limited to surface-level plausibility, lacking a coherent and unified understanding of the world. Prior approaches typically incorporate only a single form of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Boming Tan , Xiangdong Zhang , Ning Liao , Yuqing Zhang , Shaofeng Zhang , Xue Yang , Qi Fan , Yanyong Zhang

The vision and language generative models have been overgrown in recent years. For video generation, various open-sourced models and public-available services have been developed to generate high-quality videos. However, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yaofang Liu , Xiaodong Cun , Xuebo Liu , Xintao Wang , Yong Zhang , Haoxin Chen , Yang Liu , Tieyong Zeng , Raymond Chan , Ying Shan
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