Holistically-Attracted Wireframe Parsing
- URL: http://arxiv.org/abs/2003.01663v1
- Date: Tue, 3 Mar 2020 17:43:57 GMT
- Title: Holistically-Attracted Wireframe Parsing
- Authors: Nan Xue and Tianfu Wu and Song Bai and Fu-Dong Wang and Gui-Song Xia
and Liangpei Zhang and Philip H.S. Torr
- Abstract summary: This paper presents a fast and parsimonious parsing method to detect a vectorized wireframe in an input image with a single forward pass.
The proposed method is end-to-end trainable, consisting of three components: (i) line segment and junction proposal generation, (ii) line segment and junction matching, and (iii) line segment and junction verification.
- Score: 123.58263152571952
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper presents a fast and parsimonious parsing method to accurately and
robustly detect a vectorized wireframe in an input image with a single forward
pass. The proposed method is end-to-end trainable, consisting of three
components: (i) line segment and junction proposal generation, (ii) line
segment and junction matching, and (iii) line segment and junction
verification. For computing line segment proposals, a novel exact dual
representation is proposed which exploits a parsimonious geometric
reparameterization for line segments and forms a holistic 4-dimensional
attraction field map for an input image. Junctions can be treated as the
"basins" in the attraction field. The proposed method is thus called
Holistically-Attracted Wireframe Parser (HAWP). In experiments, the proposed
method is tested on two benchmarks, the Wireframe dataset, and the YorkUrban
dataset. On both benchmarks, it obtains state-of-the-art performance in terms
of accuracy and efficiency. For example, on the Wireframe dataset, compared to
the previous state-of-the-art method L-CNN, it improves the challenging mean
structural average precision (msAP) by a large margin ($2.8\%$ absolute
improvements) and achieves 29.5 FPS on single GPU ($89\%$ relative
improvement). A systematic ablation study is performed to further justify the
proposed method.
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