2.5k citations · 9.9k across the 27 of their papers we have counts for
6 papers · 1 filter
Metric Learning with Adaptive Density Discrimination
Oren Rippel, Manohar Paluri, Piotr Dollar +1
Distance metric learning (DML) approaches learn a transformation to a representation space where distance is in correspondence with a predefined notion of similarity. While such mo…
Unsupervised Learning of Edges
Yin Li, Manohar Paluri, James M. Rehg +1
Data-driven approaches for edge detection have proven effective and achieve top results on modern benchmarks. However, all current data-driven edge detectors require manual supervi…
Semantic Amodal Segmentation
Yan Zhu, Yuandong Tian, Dimitris Mexatas +1
Common visual recognition tasks such as classification, object detection, and semantic segmentation are rapidly reaching maturity, and given the recent rate of progress, it is not…
Learning to Segment Object Candidates
Pedro O. Pinheiro, Ronan Collobert, Piotr Dollar
Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of candidate proposals is then p…
Microsoft COCO Captions: Data Collection and Evaluation Server
Xinlei Chen, Hao Fang, Tsung-Yi Lin +4
In this paper we describe the Microsoft COCO Caption dataset and evaluation server. When completed, the dataset will contain over one and a half million captions describing over 33…
What makes for effective detection proposals?
Jan Hosang, Rodrigo Benenson, Piotr Dollár +1
Current top performing object detectors employ detection proposals to guide the search for objects, thereby avoiding exhaustive sliding window search across images. Despite the pop…