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Recently, there has been an increasing interest in developing diffusion-based text-to-image generative models capable of generating coherent and well-formed visual text. In this paper, we propose a novel and efficient approach called…

计算机视觉与模式识别 · 计算机科学 2023-11-14 Yukang Yang , Dongnan Gui , Yuhui Yuan , Weicong Liang , Haisong Ding , Han Hu , Kai Chen

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

计算机视觉与模式识别 · 计算机科学 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow users…

计算机视觉与模式识别 · 计算机科学 2023-04-28 Tsai-Shien Chen , Chieh Hubert Lin , Hung-Yu Tseng , Tsung-Yi Lin , Ming-Hsuan Yang

To reconstruct the 3D geometry from calibrated images, learning-based multi-view stereo (MVS) methods typically perform multi-view depth estimation and then fuse depth maps into a mesh or point cloud. To improve the computational…

计算机视觉与模式识别 · 计算机科学 2025-09-19 Fangjinhua Wang , Qingshan Xu , Yew-Soon Ong , Marc Pollefeys

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question of adding such controllability to text-to-3D generation. In…

计算机视觉与模式识别 · 计算机科学 2023-09-08 Sungwon Hwang , Junha Hyung , Jaegul Choo

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

计算机视觉与模式识别 · 计算机科学 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

计算机视觉与模式识别 · 计算机科学 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

计算机视觉与模式识别 · 计算机科学 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna

Traditional and neural video codecs commonly encounter limitations in controllability and generality under ultra-low-bitrate coding scenarios. To overcome these challenges, we propose M3-CVC, a controllable video compression framework…

图像与视频处理 · 电气工程与系统科学 2024-12-30 Rui Wan , Qi Zheng , Yibo Fan

Recently, text-to-3D approaches have achieved high-fidelity 3D content generation using text description. However, the generated objects are stochastic and lack fine-grained control. Sketches provide a cheap approach to introduce such…

计算机视觉与模式识别 · 计算机科学 2024-01-30 Minglin Chen , Weihao Yuan , Yukun Wang , Zhe Sheng , Yisheng He , Zilong Dong , Liefeng Bo , Yulan Guo

We propose MagicQuill V2, a novel system that introduces a \textbf{layered composition} paradigm to generative image editing, bridging the gap between the semantic power of diffusion models and the granular control of traditional graphics…

计算机视觉与模式识别 · 计算机科学 2025-12-03 Zichen Liu , Yue Yu , Hao Ouyang , Qiuyu Wang , Shuailei Ma , Ka Leong Cheng , Wen Wang , Qingyan Bai , Yuxuan Zhang , Yanhong Zeng , Yixuan Li , Xing Zhu , Yujun Shen , Qifeng Chen

The emergence of generative models has revolutionized the field of remote sensing (RS) image generation. Despite generating high-quality images, existing methods are limited in relying mainly on text control conditions, and thus do not…

计算机视觉与模式识别 · 计算机科学 2024-09-04 Datao Tang , Xiangyong Cao , Xingsong Hou , Zhongyuan Jiang , Junmin Liu , Deyu Meng

Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, crucial for 3D perception tasks, remains elusive. Specifically, utilizing Bird's-Eye…

计算机视觉与模式识别 · 计算机科学 2024-05-06 Ruiyuan Gao , Kai Chen , Enze Xie , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung , Qiang Xu

Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the…

计算机视觉与模式识别 · 计算机科学 2024-04-29 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

Recent spatial control methods for text-to-image (T2I) diffusion models have shown compelling results. However, these methods still fail to precisely follow the control conditions and generate the corresponding images, especially when…

计算机视觉与模式识别 · 计算机科学 2025-07-29 Jiaze Wang , Rui Chen , Haowang Cui

We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM) to predict semantic visual embeddings via learnable query tokens, which subsequently…

计算机视觉与模式识别 · 计算机科学 2026-04-23 Zijie Li , Yichun Shi , Jingxiang Sun , Ye Wang , Yixuan Huang , Zhiyao Guo , Xiaochen Lian , Peihao Zhu , Yu Tian , Zhonghua Zhai , Peng Wang

Deep learning is providing a wealth of new approaches to the problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end style architectures. Each approach offers specific strengths but also comes with…

计算机视觉与模式识别 · 计算机科学 2025-06-06 Bernard Spiegl , Andrea Perin , Stéphane Deny , Alexander Ilin

Generating high-quality textures for 3D assets is a challenging task. Existing multiview texture generation methods suffer from the multiview inconsistency and missing textures on unseen parts, while UV inpainting texture methods do not…

计算机视觉与模式识别 · 计算机科学 2026-03-17 Zheng Zhang , Qinchuan Zhang , Yuteng Ye , Zhi Chen , Penglei Ji , Mengfei Li , Wenxiao Zhang , Yuan Liu

With advancements in video generative AI models (e.g., SORA), creators are increasingly using these techniques to enhance video previsualization. However, they face challenges with incomplete and mismatched AI workflows. Existing methods…

计算机视觉与模式识别 · 计算机科学 2024-09-02 Yiran Chen , Anyi Rao , Xuekun Jiang , Shishi Xiao , Ruiqing Ma , Zeyu Wang , Hui Xiong , Bo Dai

In recent years, diffusion models have made remarkable strides in text-to-video generation, sparking a quest for enhanced control over video outputs to more accurately reflect user intentions. Traditional efforts predominantly focus on…

计算机视觉与模式识别 · 计算机科学 2024-07-18 Mingxiao Li , Bo Wan , Marie-Francine Moens , Tinne Tuytelaars