Multi-representations Space Separation based Graph-level Anomaly-aware Detection

1 code implementation • 22 Jul 2023 • Fu Lin, Haonan Gong, Mingkang Li, Zitong Wang, Yue Zhang, Xuexiong Luo

The previous works have observed that abnormal graphs mainly show node-level and graph-level anomalies, but these methods equally treat two anomaly forms above in the evaluation of abnormal graphs, which is contrary to the fact that different types of abnormal graph data have different degrees in terms of node-level and graph-level anomalies.

Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style

1 code implementation • CVPR 2023 • Fengyin Lin, Mingkang Li, Da Li, Timothy Hospedales, Yi-Zhe Song, Yonggang Qi

This paper studies the problem of zero-short sketch-based image retrieval (ZS-SBIR), however with two significant differentiators to prior art (i) we tackle all variants (inter-category, intra-category, and cross datasets) of ZS-SBIR with just one network (``everything''), and (ii) we would really like to understand how this sketch-photo matching operates (``explainable'').

Relation Network Retrieval +1

SketchLattice: Latticed Representation for Sketch Manipulation

no code implementations • ICCV 2021 • Yonggang Qi, Guoyao Su, Pinaki Nath Chowdhury, Mingkang Li, Yi-Zhe Song

The key challenge in designing a sketch representation lies with handling the abstract and iconic nature of sketches.