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Text-guided image editing using Text-to-Image (T2I) models often fails to yield satisfactory results, frequently introducing unintended modifications, such as the loss of local detail and color changes. In this paper, we analyze these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yufan Ren , Zicong Jiang , Tong Zhang , Søren Forchhammer , Sabine Süsstrunk

Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Shangchen Zhou , Peiqing Yang , Jianyi Wang , Yihang Luo , Chen Change Loy

Text-guided diffusion models have revolutionized image and video generation and have also been successfully used for optimization-based 3D object synthesis. Here, we instead focus on the underexplored text-to-4D setting and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Huan Ling , Seung Wook Kim , Antonio Torralba , Sanja Fidler , Karsten Kreis

Temporal modeling on regular respiration-induced motions is crucial to image-guided clinical applications. Existing methods cannot simulate temporal motions unless high-dose imaging scans including starting and ending frames exist…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Xin You , Minghui Zhang , Hanxiao Zhang , Jie Yang , Nassir Navab

Diffusion models achieve strong generative performance but often rely on large datasets that may include sensitive content. This challenge is compounded by the models' tendency to memorize training data, raising privacy concerns. SFBD (Lu…

Machine Learning · Computer Science 2026-04-07 Haoye Lu , Darren Lo , Yaoliang Yu

Feedforward Gaussian Splatting has recently emerged as an efficient paradigm for 4D reconstruction in autonomous driving. However, in unstructured off-road scenes, its performance degrades due to high-frequency geometry, ego-motion jitter,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Shuo Wang , Jilin Mei , Fuyang Liu , Wenfei Guan , Fanjie Kong , Zhihua Zhao , Shuai Wang , Chen Min , Yu Hu

We explore inference-time scaling in text-guided 3D diffusion models to enhance generative quality without additional training. To this end, we introduce ITS3D, a framework that formulates the task as an optimization problem to identify the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Zhenglin Zhou , Fan Ma , Xiaobo Xia , Hehe Fan , Yi Yang , Tat-Seng Chua

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

Image generation models trained on large datasets can synthesize high-quality images but often produce spatially inconsistent and distorted images due to limited information about the underlying structures and spatial layouts. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Hyundo Lee , Suhyung Choi , Inwoo Hwang , Byoung-Tak Zhang

Recent advances in diffusion models have demonstrated exceptional capabilities in image and video generation, further improving the effectiveness of 4D synthesis. Existing 4D generation methods can generate high-quality 4D objects or scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Bohan Zeng , Ling Yang , Siyu Li , Jiaming Liu , Zixiang Zhang , Juanxi Tian , Kaixin Zhu , Yongzhen Guo , Fu-Yun Wang , Minkai Xu , Stefano Ermon , Wentao Zhang

The emergence of text-to-image generation models has led to the recognition that image enhancement, performed as post-processing, would significantly improve the visual quality of the generated images. Exploring diffusion models to enhance…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Yang Luo , Yiheng Zhang , Zhaofan Qiu , Ting Yao , Zhineng Chen , Yu-Gang Jiang , Tao Mei

Score-based models generate samples by mapping noise to data (and vice versa) via a high-dimensional diffusion process. We question whether it is necessary to run this entire process at high dimensionality and incur all the inconveniences…

Machine Learning · Computer Science 2023-02-28 Bowen Jing , Gabriele Corso , Renato Berlinghieri , Tommi Jaakkola

Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-scene optimization. Bridging generation and novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Hao Lu , Zhuang Ma , Guangfeng Jiang , Wenhang Ge , Bohan Li , Yuzhan Cai , Wenzhao Zheng , Yunpeng Zhang , Yingcong Chen

Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences where motion causes significant geometric ambiguity. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ying Zang , Yidong Han , Chaotao Ding , Yuanqi Hu , Deyi Ji , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

In this paper, we present Diffusion-4K, a novel framework for direct ultra-high-resolution image synthesis using text-to-image diffusion models. The core advancements include: (1) Aesthetic-4K Benchmark: addressing the absence of a publicly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Jinjin Zhang , Qiuyu Huang , Junjie Liu , Xiefan Guo , Di Huang

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Although prevailing camera-controlled video generation models can produce cinematic results, lifting them directly to the generation of 3D-consistent and high-fidelity time-synchronized multi-view videos remains challenging, which is a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Qisen Wang , Yifan Zhao , Peisen Shen , Jialu Li , Jia Li

Given the high complexity of directly generating high-dimensional data such as 4D, we present 4DVD, a cascaded video diffusion model that generates 4D content in a decoupled manner. Unlike previous multi-view video methods that directly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Shuzhou Yang , Xiaodong Cun , Xiaoyu Li , Yaowei Li , Jian Zhang

Text-to-image generative models have attracted rising attention for flexible image editing via user-specified descriptions. However, text descriptions alone are not enough to elaborate the details of subjects, often compromising the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-14 Xin Zhang , Jiaxian Guo , Paul Yoo , Yutaka Matsuo , Yusuke Iwasawa

Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, and attributes. Existing inference-time strategies, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Shantanu Jaiswal , Mihir Prabhudesai , Nikash Bhardwaj , Zheyang Qin , Amir Zadeh , Chuan Li , Katerina Fragkiadaki , Deepak Pathak