TextureGAN: Controlling Deep Image Synthesis with Texture Patches

Abstract: In this paper, we investigate deep image synthesis guided by sketch, color, and texture. Previous image synthesis methods can be controlled by sketch and color strokes but we are the first to examine texture control. We allow a user to place a texture patch on a sketch at arbitrary locations and scales to control the desired output texture. Our generative network learns to synthesize objects consistent with these texture suggestions. To achieve this, we develop a local texture loss in addition to adversarial and content loss to train the generative network. We conduct experiments using sketches generated from real images and textures sampled from a separate texture database and results show that our proposed algorithm is able to generate plausible images that are faithful to user controls. Ablation studies show that our proposed pipeline can generate more realistic images than adapting existing methods directly.

• The paper proposes a novel GAN framework that integrates user-supplied texture patches to steer the synthesis process.
• It demonstrates enhanced texture consistency and detail control, improving the realism of generated images.
• Experimental results validate that the method effectively fuses texture cues with semantic content for robust image generation.

Overview of LaTeX Author Guidelines for CVPR Proceedings

The paper "LaTeX Author Guidelines for CVPR Proceedings" serves as a comprehensive manual for authors who wish to submit their work to the IEEE Computer Vision and Pattern Recognition (CVPR) conference. This document provides detailed instructions on manuscript preparation, focusing particularly on adherence to specific formatting guidelines using LaTeX. It addresses key areas such as manuscript language, dual submission policies, manuscript length restrictions, and anonymity in blind review processes. These components ensure submissions are uniformly structured, facilitating a smooth review process.

Manuscript Preparation

Authors are required to submit their manuscripts in English, maintaining a strict adherence to the formatting rules detailed in the guidelines. The paper is limited to a maximum of eight pages, excluding references, without incurring additional page charges. The document specifies the use of a two-column format, with specific dimensions for text area and spacing. Adhering strictly to these limitations is crucial, as non-compliant submissions will not be reviewed.

Blind Review and Anonymity

The guidelines emphasize the importance of maintaining anonymity during the blind review process. Authors are instructed to avoid self-referential expressions such as "my" or "our" in citations of their prior work. This practice ensures the objectivity of the review, even though it acknowledges that reviewers may infer the authorship based on context and content familiarity.

Formatting Specifications

The paper meticulously details typographic and layout requirements, including font styles and sizes for different sections. Emphasis is placed on maintaining consistency across all illustrative materials, such as figures and tables, to align with the document's overall aesthetic. The inclusion of technical elements, such as equations and algorithms, necessitates precise formatting and, where possible, the use of appropriate LaTeX commands to maintain clarity and coherence.

Additional Considerations

Other elements discussed in the guidelines include the implementation of a printed ruler for feedback specificity, recommendations for mathematical writing, variations in citation styles, and footnote usage minimization. These directly contribute to paper readability and standardization, aligning with CVPR's high academic and presentation standards.

Implications and Future Directions

The structured framework outlined in this paper highlights the importance of uniformity and precision in academic publishing within the computer vision community. While primarily administrative, these guidelines contribute to the broader discourse on academic transparency and reproducibility, laying the groundwork for potential future innovations in automated manuscript submission and review processes in AI research. As AI continues to evolve, opportunities may arise to refine these guidelines to incorporate more dynamic and interactive document elements, potentially enhancing both the authoring experience and the review process.

In summary, the "LaTeX Author Guidelines for CVPR Proceedings" document acts as a critical resource for ensuring clarity, consistency, and fairness in the review of submissions to the CVPR conference, supporting the dissemination of high-quality research outputs.