Symbol as Points: Panoptic Symbol Spotting via Point-based Representation

This work studies the problem of panoptic symbol spotting, which is to spot and parse both countable object instances (windows, doors, tables, etc.) and uncountable stuff (wall, railing, etc.) from computer-aided design (CAD) drawings. Existing methods typically involve either rasterizing the vector graphics into images and using image-based methods for symbol spotting, or directly building graphs and using graph neural networks for symbol recognition. In this paper, we take a different approach, which treats graphic primitives as a set of 2D points that are locally connected and use point cloud segmentation methods to tackle it. Specifically, we utilize a point transformer to extract the primitive features and append a mask2former-like spotting head to predict the final output. To better use the local connection information of primitives and enhance their discriminability, we further propose the attention with connection module (ACM) and contrastive connection learning scheme (CCL). Finally, we propose a KNN interpolation mechanism for the mask attention module of the spotting head to better handle primitive mask downsampling, which is primitive-level in contrast to pixel-level for the image. Our approach, named SymPoint, is simple yet effective, outperforming recent state-of-the-art method GAT-CADNet by an absolute increase of 9.6% PQ and 10.4% RQ on the FloorPlanCAD dataset. The source code and models will be available at https://github.com/nicehuster/SymPoint.Comment: ICLR 202

Minimality for puncturing convolutional codes

This paper investigates encoders optimization for the Hamming weight after periodic puncturing, and discusses minimality issues that may affect the performance of the punctured encoders. Periodically puncturing a minimal encoder produces a higher rate encoder that may or may not be minimal. If it is not minimal, it may have a zero-output loop and it may be catastrophic. A code search can use a fast algorithm to determine whether an encoder's state diagram has a zero-output loop under periodic symbol puncturing, and a proposed method to assess the performance of codes with a zero-output loop that are not catastrophic. As an example, the paper optimizes rate-1/4 unpunctured codes for Hamming weight under both bit-wise and symbol-wise periodic puncturing. Code tables and simulation results are included

A Machine-Independent Debugger--Revisited

Most debuggers are notoriously machine-dependent, but some recent research prototypes achieve varying degrees of machine-independence with novel designs. Cdb, a simple source-level debugger for C, is completely independent of its target architecture. This independence is achieved by embedding symbol tables and debugging code in the target program, which costs both time and space. This paper describes a revised design and implementation of cdb that reduces the space cost by nearly one-half and the time cost by 13% by storing symbol tables in external files. A symbol table is defined by a 31-line grammar in the Abstract Syntax Description Language (ASDL). ASDL is a domain-specific language for specifying tree data structures. The ASDL tools accept an ASDL grammar and generate code to construct, read, and write these data structures. Using ASDL automates implementing parts of the debugger, and the grammar documents the symbol table concisely. Using ASDL also suggested simplifications to the interface between the debugger and the target program. Perhaps most important, ASDL emphasizes that symbol tables are data structures, not file formats. Many of the pitfalls of working with low-level file formats can be avoided by focusing instead on high-level data structures and automating the implementation details.Comment: 12 pages; 6 figures; 3 table