activity
20162020
most citedRethinking Feature Discrimination and Polymerization for Large-scale Recognition

112 citations · 302 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2020

Exploring intermediate representation for monocular vehicle pose estimation

Shichao Li, Zengqiang Yan, Hongyang Li +1

We present a new learning-based framework to recover vehicle pose in SO(3) from a single RGB image. In contrast to previous works that map from local appearance to observation angl…

cs.CV201995 cited

Finding Task-Relevant Features for Few-Shot Learning by Category Traversal

Hongyang Li, David Eigen, Samuel Dodge +2

Few-shot learning is an important area of research. Conceptually, humans are readily able to understand new concepts given just a few examples, while in more pragmatic terms, limit…

cs.CV201914 cited

Feature Intertwiner for Object Detection

Hongyang Li, Bo Dai, Shaoshuai Shi +2

A well-trained model should classify objects with a unanimous score for every category. This requires the high-level semantic features should be as much alike as possible among sam…

cs.LG2018

Neural Network Encapsulation

Hongyang Li, Xiaoyang Guo, Bo Dai +2

A capsule is a collection of neurons which represents different variants of a pattern in the network. The routing scheme ensures only certain capsules which resemble lower counterp…

cs.CV2017112 cited

Rethinking Feature Discrimination and Polymerization for Large-scale Recognition

Yu Liu, Hongyang Li, Xiaogang Wang

Feature matters. How to train a deep network to acquire discriminative features across categories and polymerized features within classes has always been at the core of many comput…

cs.CV201756 cited

Learning Deep Features via Congenerous Cosine Loss for Person Recognition

Yu Liu, Hongyang Li, Xiaogang Wang

Person recognition aims at recognizing the same identity across time and space with complicated scenes and similar appearance. In this paper, we propose a novel method to address t…