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20172022
most citedLearning and Evaluating Representations for Deep One-class Classification

93 citations · 122 across the 9 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021★ 2 cited

Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types

Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li +2

We study anomaly clustering, grouping data into coherent clusters of anomaly types. This is different from anomaly detection that aims to divide anomalies from normal data. Unlike…

cs.CV2021

Robust Contrastive Learning Using Negative Samples with Diminished Semantics

Songwei Ge, Shlok Mishra, Haohan Wang +2

Unsupervised learning has recently made exceptional progress because of the development of more effective contrastive learning methods. However, CNNs are prone to depend on low-lev…

cs.CV2021★ 16 cited

Object-aware Contrastive Learning for Debiased Scene Representation

Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn +2

Contrastive self-supervised learning has shown impressive results in learning visual representations from unlabeled images by enforcing invariance against different data augmentati…

cs.CL2021

ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction

Chen-Yu Lee, Chun-Liang Li, Chu Wang +5

Natural reading orders of words are crucial for information extraction from form-like documents. Despite recent advances in Graph Convolutional Networks (GCNs) on modeling spatial…

cs.LG2021

DISSECT: Disentangled Simultaneous Explanations via Concept Traversals

Asma Ghandeharioun, Been Kim, Chun-Liang Li +3

Explaining deep learning model inferences is a promising venue for scientific understanding, improving safety, uncovering hidden biases, evaluating fairness, and beyond, as argued…