2 citations · 2 across the 5 of their papers we have counts for
5 papers
LMPNet for Weakly-supervised Keypoint Discovery
Pei Guo, Ryan Farrell
In this work, we explore the task of semantic object keypoint discovery weakly-supervised by only category labels. This is achieved by transforming discriminatively-trained interme…
Enhanced Information Fusion Network for Crowd Counting
Geng Chen, Peirong Guo
In recent years, crowd counting, a technique for predicting the number of people in an image, becomes a challenging task in computer vision. In this paper, we propose a cross-colum…
Semantic Network Interpretation
Pei Guo, Ryan Farrell
Network interpretation as an effort to reveal the features learned by a network remains largely visualization-based. In this paper, our goal is to tackle semantic network interpret…
Aligned to the Object, not to the Image: A Unified Pose-aligned Representation for Fine-grained Recognition
Pei Guo, Ryan Farrell
Dramatic appearance variation due to pose constitutes a great challenge in fine-grained recognition, one which recent methods using attention mechanisms or second-order statistics…
Pairwise Confusion for Fine-Grained Visual Classification
Abhimanyu Dubey, Otkrist Gupta, Pei Guo +3
Fine-Grained Visual Classification (FGVC) datasets contain small sample sizes, along with significant intra-class variation and inter-class similarity. While prior work has address…