213 citations · 242 across the 5 of their papers we have counts for
5 papers
Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection
Carlo Biffi, Steven McDonagh, Philip Torr +2
Object detection has witnessed significant progress by relying on large, manually annotated datasets. Annotating such datasets is highly time consuming and expensive, which motivat…
Revisiting Anchor Mechanisms for Temporal Action Localization
Le Yang, Houwen Peng, Dingwen Zhang +2
Most of the current action localization methods follow an anchor-based pipeline: depicting action instances by pre-defined anchors, learning to select the anchors closest to the gr…
Equivalent Classification Mapping for Weakly Supervised Temporal Action Localization
Tao Zhao, Junwei Han, Le Yang +1
Weakly supervised temporal action localization is a newly emerging yet widely studied topic in recent years. The existing methods can be categorized into two localization-by-classi…
PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection
Nian Liu, Junwei Han, Ming-Hsuan Yang
In saliency detection, every pixel needs contextual information to make saliency prediction. Previous models usually incorporate contexts holistically. However, for each pixel, usu…
A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection
Nian Liu, Junwei Han
Traditional saliency models usually adopt hand-crafted image features and human-designed mechanisms to calculate local or global contrast. In this paper, we propose a novel computa…