OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion (2302.13540v1)

Abstract: 3D Semantic Scene Completion (SSC) can provide dense geometric and semantic scene representations, which can be applied in the field of autonomous driving and robotic systems. It is challenging to estimate the complete geometry and semantics of a scene solely from visual images, and accurate depth information is crucial for restoring 3D geometry. In this paper, we propose the first stereo SSC method named OccDepth, which fully exploits implicit depth information from stereo images (or RGBD images) to help the recovery of 3D geometric structures. The Stereo Soft Feature Assignment (Stereo-SFA) module is proposed to better fuse 3D depth-aware features by implicitly learning the correlation between stereo images. In particular, when the input are RGBD image, a virtual stereo images can be generated through original RGB image and depth map. Besides, the Occupancy Aware Depth (OAD) module is used to obtain geometry-aware 3D features by knowledge distillation using pre-trained depth models. In addition, a reformed TartanAir benchmark, named SemanticTartanAir, is provided in this paper for further testing our OccDepth method on SSC task. Compared with the state-of-the-art RGB-inferred SSC method, extensive experiments on SemanticKITTI show that our OccDepth method achieves superior performance with improving +4.82% mIoU, of which +2.49% mIoU comes from stereo images and +2.33% mIoU comes from our proposed depth-aware method. Our code and trained models are available at https://github.com/megvii-research/OccDepth.

• The paper presents OccDepth, a novel method that leverages depth cues and occlusion reasoning to improve 3D semantic scene completion.
• The paper employs an innovative mechanism to integrate precise depth estimation for accurate reconstruction of incomplete scene geometry.
• The paper demonstrates enhanced performance and robustness in 3D scene reconstruction, underscoring its potential for advanced robotics and vision applications.

Review of IJCAI--23 Formatting Instructions Paper

The paper "IJCAI--23 Formatting Instructions" provides a comprehensive overview of the author guidelines and formatting requirements for the submission of manuscripts to the IJCAI-23 conference. The document serves as a procedural and instructional guide to ensure uniformity and consistency in the presentation of research papers meant for the conference proceedings.

Overview and Structure

The document begins with an abstract, specifying its purpose as a guideline for authors to prepare electronic manuscripts for both submission and eventual publication in the conference proceedings. Followed by this, the format instructions delve into the specifics of paper length, word processing software compatibility, and the required style and format. The authors emphasize the need for adherence to a structured layout with specific margins, column width settings, and use of Adobe's Portable Document Format (PDF).

Key Formatting Specifications

Key technical specifications detailed in the paper include:

• Length of Papers: Authors are provided stringent limits on paper length. Seven pages are allocated for content, with two additional pages permissible for references and other ancillary disclosures.
• Anonymity and Blind Review: The paper details conditions under which author anonymity is required during submission, particularly in review tracks demanding blind submissions.
• Section and Subsection Formatting: Detailed instructions on how titles, authors, affiliations, and emails should be formatted to maintain consistency.
• Abstract and Main Text: Guidelines on how the abstract and main body should be structured, including font specifications and indentation practices.
• Illustrations, Tables, and Formulae: Recommendations on how to incorporate illustrations, tables, and complex equations, with a focus on clarity and readability.

Implications and Future Considerations

From a practical standpoint, such detailed formatting guidelines ensure that submissions are homogenous, making both the review process and indexing more efficient. The emphasis on consistent formatting could also minimize barriers to entry for less experienced researchers by providing a clear template to conform to. Theoretically, this consistency aids in producing a cohesive and professional conference proceedings package.

Looking forward, these detailed formatting requirements could presage the implementation of automated manuscript formatting tools that pre-vet submissions for conformity. As advances in AI for document processing evolve, one could envision further integration of these technologies within submission platforms, enhancing the convenience for authors and editors alike.

The paper is primarily procedural and technical. However, it lays a necessary foundation for a well-structured approach to academic publishing, simplifying the path for new research insights to be properly shared within the community. Ensuring widespread adherence to such guides is crucial in maintaining the integrity and accessibility of scholarly communication.