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In real-world images, slanted or curved texts, especially those on cans, banners, or badges, appear as frequently, if not more so, than flat texts due to artistic design or layout constraints. While high-quality visual text generation has…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Minxing Luo , Zixun Xia , Liaojun Chen , Zhenhang Li , Weichao Zeng , Jianye Wang , Wentao Cheng , Yaxing Wang , Yu Zhou , Jian Yang

Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo

Existing multi-agent video generation systems use LLM agents to orchestrate neural video generators, producing visually impressive but semantically unreliable outputs with no ground truth annotations. We present an agentic system that…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Nicolae Cudlenco , Mihai Masala , Marius Leordeanu

Text-to-video generation has trailed behind text-to-image generation in terms of quality and diversity, primarily due to the inherent complexities of spatio-temporal modeling and the limited availability of video-text datasets. Recent…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Xiefan Guo , Jinlin Liu , Miaomiao Cui , Liefeng Bo , Di Huang

We present a method for text-driven perpetual view generation -- synthesizing long-term videos of various scenes solely, given an input text prompt describing the scene and camera poses. We introduce a novel framework that generates such…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Rafail Fridman , Amit Abecasis , Yoni Kasten , Tali Dekel

This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works that lack support for unified shared world construction with multi-agent interaction. ShareVerse…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiayi Zhu , Jianing Zhang , Yiying Yang , Wei Cheng , Xiaoyun Yuan

Existing dynamic scene generation methods mostly rely on distilling knowledge from pre-trained 3D generative models, which are typically fine-tuned on synthetic object datasets. As a result, the generated scenes are often object-centric and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Heng Yu , Chaoyang Wang , Peiye Zhuang , Willi Menapace , Aliaksandr Siarohin , Junli Cao , Laszlo A Jeni , Sergey Tulyakov , Hsin-Ying Lee

Given the remarkable ability of 2D foundation image models to generate high-fidelity outputs, we investigate a fundamental question: do 2D foundation image models inherently possess 3D world model capabilities? To answer this, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Ziya Erkoç , Angela Dai , Matthias Nießner

We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural world. Infinigen is entirely procedural: every asset, from shape to texture, is generated from scratch via randomized mathematical rules, using no…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Alexander Raistrick , Lahav Lipson , Zeyu Ma , Lingjie Mei , Mingzhe Wang , Yiming Zuo , Karhan Kayan , Hongyu Wen , Beining Han , Yihan Wang , Alejandro Newell , Hei Law , Ankit Goyal , Kaiyu Yang , Jia Deng

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transformer backbones. Although there have been efforts to control…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Liang Chen , Shuai Bai , Wenhao Chai , Weichu Xie , Haozhe Zhao , Leon Vinci , Junyang Lin , Baobao Chang

Large-scale diffusion models have achieved remarkable success in generating high-quality images from textual descriptions, gaining popularity across various applications. However, the generation of layered content, such as transparent…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Yusuf Dalva , Yijun Li , Qing Liu , Nanxuan Zhao , Jianming Zhang , Zhe Lin , Pinar Yanardag

The ability to automatically generate large-scale, interactive, and physically realistic 3D environments is crucial for advancing robotic learning and embodied intelligence. However, existing generative approaches often fail to capture the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 ChunTeng Chen , YiChen Hsu , YiWen Liu , WeiFang Sun , TsaiChing Ni , ChunYi Lee , Min Sun , YuanFu Yang

Recent advances in image generation have achieved remarkable visual quality, while a fundamental challenge remains: Can image generation be controlled at the element level, enabling intuitive modifications such as adjusting shapes, altering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Lanqing Guo , Xi Liu , Yufei Wang , Zhihao Li , Siyu Huang

Recent advancements in image-conditioned image generation have demonstrated substantial progress. However, foreground-conditioned image generation remains underexplored, encountering challenges such as compromised object integrity,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Tianyidan Xie , Rui Ma , Qian Wang , Xiaoqian Ye , Feixuan Liu , Ying Tai , Zhenyu Zhang , Lanjun Wang , Zili Yi

Generating controllable and physically plausible indoor scenes is a pivotal prerequisite for constructing high-fidelity simulation environments for embodied AI. However, existing deeplearning-based methods usually treat all objects as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Zini Chen , Junming Huang , Rong Zhang , Jiamin Xu , Cheng Peng , Chi Wang , Weiwei Xu

Generating high-quality physically based rendering (PBR) materials is important to achieve realistic rendering in the downstream tasks, yet it remains challenging due to the intertwined effects of materials and lighting. While existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xiaokang Wei , Bowen Zhang , Xianghui Yang , Yuxuan Wang , Chunchao Guo , Xi Zhao , Yan Luximon

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…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Yiran Chen , Anyi Rao , Xuekun Jiang , Shishi Xiao , Ruiqing Ma , Zeyu Wang , Hui Xiong , Bo Dai

There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from…

Artificial Intelligence · Computer Science 2024-09-24 Nels Numan , Shwetha Rajaram , Balasaravanan Thoravi Kumaravel , Nicolai Marquardt , Andrew D. Wilson

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun
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