Sign inGet started
Paper · arXiv

Enhanced Deformable Convolution with Center-invariant Offset and Edge-aware Mask

Deformable convolution networks have recently become popular for many computer vision tasks, especially for semantic segmentation, because of their exceptional capabilities in dynamic spatial modeling. However, due to the dense deformable offsets and the lack of longer-range dependencies, they can not fully adopt proper and precise deformations for feature representations. To tackle the issues, in this paper, we propose Enhanced Deformable ConvNets (EDCN) for semantic segmentation. Specifically, a novel Enhanced Deformable Convolution (EDC) is exploited in the decoder, which integrates the Center-invariant Offset Module (COM) and Edge-aware Mask Module (EMM). The COM employs larger kernel...

AuthorsYixiao Li, Xiaoyuan Yang, Jin Jiang et al.
Primary categorycs.CV
Published9 September 2026
Last updated at source11 September 2026
cs.CV
Embed this entry
<iframe src="https://silytics.si/embed/item/d44e5782-e94c-4a46-9324-f06d43a70792" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.