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Evaluating Generative 3D models remains challenging due to misalignment between automated metrics and human perception of quality. Current benchmarks rely on image-based metrics that ignore 3D structure or geometric measures that fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Dylan Ebert

Text-to-3D (T23D) generation has emerged as a crucial visual generation task, aiming at synthesizing 3D content from textual descriptions. Studies of this task are currently shifting from per-scene T23D, which requires optimization of the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Xiao Cai , Sitong Su , Jingkuan Song , Pengpeng Zeng , Ji Zhang , Qinhong Du , Mengqi Li , Heng Tao Shen , Lianli Gao

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ziqi Huang , Yinan He , Jiashuo Yu , Fan Zhang , Chenyang Si , Yuming Jiang , Yuanhan Zhang , Tianxing Wu , Qingyang Jin , Nattapol Chanpaisit , Yaohui Wang , Xinyuan Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

The rapid evolution of Large Language Models (LLMs) has fostered diverse paradigms for automated slide generation, ranging from code-driven layouts to image-centric synthesis. However, evaluating these heterogeneous systems remains…

Computation and Language · Computer Science 2026-01-15 Yunqiao Yang , Wenbo Li , Houxing Ren , Zimu Lu , Ke Wang , Zhiyuan Huang , Zhuofan Zong , Mingjie Zhan , Hongsheng Li

Video generation assessment is essential for ensuring that generative models produce visually realistic, high-quality videos while aligning with human expectations. Current video generation benchmarks fall into two main categories:…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Hui Han , Siyuan Li , Jiaqi Chen , Yiwen Yuan , Yuling Wu , Chak Tou Leong , Hanwen Du , Junchen Fu , Youhua Li , Jie Zhang , Chi Zhang , Li-jia Li , Yongxin Ni

Evaluating the performance of Multi-modal Large Language Models (MLLMs), integrating both point cloud and language, presents significant challenges. The lack of a comprehensive assessment hampers determining whether these models truly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Junjie Zhang , Tianci Hu , Xiaoshui Huang , Yongshun Gong , Dan Zeng

Personalized image generation holds great promise in assisting humans in everyday work and life due to its impressive ability to creatively generate personalized content across various contexts. However, current evaluations either are…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yuang Peng , Yuxin Cui , Haomiao Tang , Zekun Qi , Runpei Dong , Jing Bai , Chunrui Han , Zheng Ge , Xiangyu Zhang , Shu-Tao Xia

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziqi Huang , Fan Zhang , Xiaojie Xu , Yinan He , Jiashuo Yu , Ziyue Dong , Qianli Ma , Nattapol Chanpaisit , Chenyang Si , Yuming Jiang , Yaohui Wang , Xinyuan Chen , Ying-Cong Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF. Notably, these methods are able to produce high-quality 3D scenes without training on 3D data. Due to the open-ended nature of the task, most…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Yuze He , Yushi Bai , Matthieu Lin , Wang Zhao , Yubin Hu , Jenny Sheng , Ran Yi , Juanzi Li , Yong-Jin Liu

The recent advances in text and image synthesis show a great promise for the future of generative models in creative fields. However, a less explored area is the one of 3D model generation, with a lot of potential applications to game…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Antoine Schnepf , Flavian Vasile , Ugo Tanielian

Video generation has advanced rapidly, improving evaluation methods, yet assessing video's motion remains a major challenge. Specifically, there are two key issues: 1) current motion metrics do not fully align with human perceptions; 2) the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Xinran Ling , Chen Zhu , Meiqi Wu , Hangyu Li , Xiaokun Feng , Cundian Yang , Aiming Hao , Jiashu Zhu , Jiahong Wu , Xiangxiang Chu

Generative AI has made remarkable strides to revolutionize fields such as image and video generation. These advancements are driven by innovative algorithms, architecture, and data. However, the rapid proliferation of generative models has…

Artificial Intelligence · Computer Science 2024-11-12 Dongfu Jiang , Max Ku , Tianle Li , Yuansheng Ni , Shizhuo Sun , Rongqi Fan , Wenhu Chen

Rapid advances in audio-video (AV) generation have enabled high-fidelity synthesis with synchronized sound, particularly for human-related scenarios involving speech and interactions. Yet evaluation for AV generation remains at an early…

Artificial Intelligence · Computer Science 2026-05-26 Jialiang Yang , Bin Xia , Ruihang Chu , Dingdong Wang , Wanke Xia , Zhun Mou , Tianyang Zhong , Yiting Zhao , Wenming Yang

The growing interest in automatic survey generation (ASG), a task that traditionally required considerable time and effort, has been spurred by recent advances in large language models (LLMs). With advancements in retrieval-augmented…

Computation and Language · Computer Science 2025-08-18 Beichen Guo , Zhiyuan Wen , Yu Yang , Peng Gao , Ruosong Yang , Jiaxing Shen

Graphic layouts serve as an important and engaging medium for visual communication across different channels. While recent layout generation models have demonstrated impressive capabilities, they frequently fail to align with nuanced human…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Varun Gopal , Rishabh Jain , Aradhya Mathur , Nikitha SR , Sohan Patnaik , Sudhir Yarram , Mayur Hemani , Balaji Krishnamurthy , Mausoom Sarkar

Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiable rendering have enabled the training of 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Zhangyang Xiong , Di Kang , Derong Jin , Weikai Chen , Linchao Bao , Shuguang Cui , Xiaoguang Han

World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct realistic, dynamic, and physically consistent 3D/4D worlds from…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yiting Lu , Wei Luo , Peiyan Tu , Haoran Li , Hanxin Zhu , Zihao Yu , Xingrui Wang , Xinyi Chen , Xinge Peng , Xin Li , Zhibo Chen

Humans can intuitively compose and arrange scenes in the 3D space for photography. However, can advanced AI image generators plan scenes with similar 3D spatial awareness when creating images from text or image prompts? We present GenSpace,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Zehan Wang , Jiayang Xu , Ziang Zhang , Tianyu Pang , Chao Du , Hengshuang Zhao , Zhou Zhao

We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3D shapes and textures in under a minute. It supports…

Evaluation plays a crucial role in the advancement of information retrieval (IR) models. However, current benchmarks, which are based on predefined domains and human-labeled data, face limitations in addressing evaluation needs for emerging…

Information Retrieval · Computer Science 2025-07-25 Jianlyu Chen , Nan Wang , Chaofan Li , Bo Wang , Shitao Xiao , Han Xiao , Hao Liao , Defu Lian , Zheng Liu
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