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Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt view direction and mainly handle object-centric cases. In…

计算机视觉与模式识别 · 计算机科学 2025-10-14 Yuanhao Cai , He Zhang , Kai Zhang , Yixun Liang , Mengwei Ren , Fujun Luan , Qing Liu , Soo Ye Kim , Jianming Zhang , Zhifei Zhang , Yuqian Zhou , Yulun Zhang , Xiaokang Yang , Zhe Lin , Alan Yuille

Recent advances in generative diffusion models have shown a notable inherent understanding of image style and semantics. In this paper, we leverage the self-attention features from pretrained diffusion networks to transfer the visual…

计算机视觉与模式识别 · 计算机科学 2025-02-28 Yang Zhou , Xu Gao , Zichong Chen , Hui Huang

Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model generation are restricted to low resolutions with suboptimal…

计算机视觉与模式识别 · 计算机科学 2025-04-30 Yihang Luo , Shangchen Zhou , Yushi Lan , Xingang Pan , Chen Change Loy

Face stylization refers to the transformation of a face into a specific portrait style. However, current methods require the use of example-based adaptation approaches to fine-tune pre-trained generative models so that they demand lots of…

计算机视觉与模式识别 · 计算机科学 2023-12-06 Jin Liu , Huaibo Huang , Chao Jin , Ran He

Style transfer of 3D faces has gained more and more attention. However, previous methods mainly use images of artistic faces for style transfer while ignoring arbitrary style images such as abstract paintings. To solve this problem, we…

计算机视觉与模式识别 · 计算机科学 2023-03-15 Xiangwen Deng , Yingshuang Zou , Yuanhao Cai , Chendong Zhao , Yang Liu , Zhifang Liu , Yuxiao Liu , Jiawei Zhou , Haoqian Wang

Recently, methods have been proposed that perform texture synthesis and style transfer by using convolutional neural networks (e.g. Gatys et al. [2015,2016]). These methods are exciting because they can in some cases create results with…

图形学 · 计算机科学 2017-02-09 Eric Risser , Pierre Wilmot , Connelly Barnes

Text-to-3D generation has achieved significant success by incorporating powerful 2D diffusion models, but insufficient 3D prior knowledge also leads to the inconsistency of 3D geometry. Recently, since large-scale multi-view datasets have…

计算机视觉与模式识别 · 计算机科学 2024-05-03 Junyoung Seo , Susung Hong , Wooseok Jang , Inès Hyeonsu Kim , Minseop Kwak , Doyup Lee , Seungryong Kim

Hairstyles are intricate and culturally significant with various geometries, textures, and structures. Existing text or image-guided generation methods fail to handle the richness and complexity of diverse styles. We present TANGLED, a…

计算机视觉与模式识别 · 计算机科学 2025-02-11 Pengyu Long , Zijun Zhao , Min Ouyang , Qingcheng Zhao , Qixuan Zhang , Wei Yang , Lan Xu , Jingyi Yu

Garment sewing patterns are fundamental design elements that bridge the gap between design concepts and practical manufacturing. The generative modeling of sewing patterns is crucial for creating diversified garments. However, existing…

计算机视觉与模式识别 · 计算机科学 2025-09-23 Xinyu Li , Qi Yao , Yuanda Wang

Recent developments in 3D Gaussian Splatting have significantly enhanced novel view synthesis, yet generating high-quality renderings from extreme novel viewpoints or partially observed regions remains challenging. Meanwhile, diffusion…

计算机视觉与模式识别 · 计算机科学 2025-08-21 Jiaxin Wei , Stefan Leutenegger , Simon Schaefer

This paper explores image editing under the joint control of text and drag interactions. While recent advances in text-driven and drag-driven editing have achieved remarkable progress, they suffer from complementary limitations: text-driven…

计算机视觉与模式识别 · 计算机科学 2025-09-29 Qihang Wang , Yaxiong Wang , Lechao Cheng , Zhun Zhong

Generic image inpainting aims to complete a corrupted image by borrowing surrounding information, which barely generates novel content. By contrast, multi-modal inpainting provides more flexible and useful controls on the inpainted content,…

计算机视觉与模式识别 · 计算机科学 2023-03-07 Shaoan Xie , Zhifei Zhang , Zhe Lin , Tobias Hinz , Kun Zhang

This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene…

计算机视觉与模式识别 · 计算机科学 2024-11-08 Jun-Kun Chen , Yu-Xiong Wang

Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as…

计算机视觉与模式识别 · 计算机科学 2024-06-14 Emmanuelle Bourigault , Pauline Bourigault

In this work, we focus on zero-shot 3D style transfer that can generate multi-view consistent stylized views of the 3D scene given an arbitrary style image. We primarily tackle the issue of data scarcity in 3D style transfer, which arises…

计算机视觉与模式识别 · 计算机科学 2026-05-29 Xin Dong , Yunzhi Teng , Wenfeng Deng , Yansong Tang

This paper proposes Instruct 4D-to-4D that achieves 4D awareness and spatial-temporal consistency for 2D diffusion models to generate high-quality instruction-guided dynamic scene editing results. Traditional applications of 2D diffusion…

计算机视觉与模式识别 · 计算机科学 2024-06-14 Linzhan Mou , Jun-Kun Chen , Yu-Xiong Wang

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

计算机视觉与模式识别 · 计算机科学 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual urban navigation and autonomous driving. To address this, this paper proposes MeSS…

计算机视觉与模式识别 · 计算机科学 2026-01-06 Xuyang Chen , Zhijun Zhai , Kaixuan Zhou , Zengmao Wang , Jianan He , Dong Wang , Yanfeng Zhang , mingwei Sun , Rüdiger Westermann , Konrad Schindler , Liqiu Meng

Precise spatial control in diffusion-based style transfer remains challenging. This challenge arises because diffusion models treat style as a global feature and lack explicit spatial grounding of style representations, making it difficult…

计算机视觉与模式识别 · 计算机科学 2026-02-24 Bowen Chen , Jake Zuena , Alan C. Bovik , Divya Kothandaraman

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

计算机视觉与模式识别 · 计算机科学 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel