MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions (2104.13325v2)

Abstract: Deep learning has made significant impacts on multi-view stereo systems. State-of-the-art approaches typically involve building a cost volume, followed by multiple 3D convolution operations to recover the input image's pixel-wise depth. While such end-to-end learning of plane-sweeping stereo advances public benchmarks' accuracy, they are typically very slow to compute. We present \ouralg, a highly efficient multi-view stereo algorithm that seamlessly integrates multi-view constraints into single-view networks via an attention mechanism. Since \ouralg only builds on 2D convolutions, it is at least $2\times$ faster than all the notable counterparts. Moreover, our algorithm produces precise depth estimations and 3D reconstructions, achieving state-of-the-art results on challenging benchmarks ScanNet, SUN3D, RGBD, and the classical DTU dataset. our algorithm also out-performs all other algorithms in the setting of inexact camera poses. Our code is released at \url{https://github.com/zhenpeiyang/MVS2D}

• The paper introduces an efficient multi-view stereo method that uses attention-driven 2D convolutions to enhance reconstruction accuracy.
• It presents a novel architecture that reduces computational load by focusing on key image features for improved performance.
• Experimental results show state-of-the-art performance on benchmark datasets, underlining its practical efficacy in stereo reconstruction.

Examination of the CVPR Proceedings Author Guidelines Document

The paper under discussion provides a comprehensive guideline for authors intending to submit manuscripts for the CVPR proceedings. This instructional document mainly emphasizes formatting, styling, and procedural protocols that align with the standards of the IEEE Computer Society Press. Such guidance is crucial for authors to ensure uniformity and quality in conference proceedings presentation.

Key Points and Implications

The document meticulously outlines several components essential for the submission of a manuscript. Highlighted below are significant elements and their implications:

1. Language and Submission Policies: The paper reaffirms that all manuscripts must be presented in English, adhering to the dual submission policy which discourages simultaneous submissions of the same work to different venues. This ensures that the content is original and exclusive to the CVPR conference.
2. Paper Length: A strict limitation is placed on the body of the paper to eight pages, excluding references. Notably, there are no extra page charges for CVPR 2022, a policy that provides inclusivity by removing financial barriers to submission. Overlength papers are unequivocally rejected to maintain consistency in review workload and to uphold the integrity of the review process.
3. Blind Review Process: Authors are instructed on proper anonymization techniques to facilitate a blind review process. Clarity is provided on referencing prior work without revealing the identity of the authors. This ensures an unbiased review by eliminating potential identification clues from the paper itself.
4. Formatting and Margins: The guide specifies detailed instructions on formatting aspects including margins, columns, and pagination. The use of a two-column format adheres to traditional academic presentation standards, optimizing readability and consistency.
5. Type Style and Fonts: The usage of specified fonts and sizes is outlined, ensuring visual coherence across submissions. Particular emphasis is placed on the appearance of titles, authorship information, and primary content in the Times typeface, a widely available and legible font.
6. Technical Precision: Authors are directed to number sections and equations, facilitating easier reference and discussion of technical components. This component underscores the importance of precision and traceability in scientific discourse.
7. Supplemental Material and Technical Reports: Authors are encouraged to ensure the paper stands alone without necessitating external documentation for understanding. This places emphasis on delivering a comprehensive discourse within the page limits, promoting self-sufficiency in the presentation of the work.
8. Illustrations and Graphical Content: The document provides recommendations on the preparation and integration of visual content, stressing the importance of clear and legible illustrations that complement the textual material.

Future Prospects

The implications of such detailed guidelines are manifold. Practically, they standardize submissions which facilitate a streamlined review process and improve the overall quality of published proceedings. Theoretically, adherence to these structured guidelines aids in maintaining the scientific rigor and dissemination quality associated with CVPR.

Looking forward, the author guidelines present the possibility for further enhancements, such as accommodating evolving multimedia elements in submissions and refining accessibility considerations, particularly for individuals with visual impairments. Furthermore, as AI integration in document processing advances, future iterations of such guidelines might incorporate automation tools to assist authors in aligning their submissions with these stringent formatting requirements, thereby reducing the cognitive load associated with manual formatting checks. Overall, this document serves as a foundational framework ensuring ongoing excellence in the submission and review process for scientific papers within the computer vision community.