Search Results for author: Ruichi Yu

Found 12 papers, 2 papers with code

Uncertainty Modeling of Contextual-Connections between Tracklets for Unconstrained Video-based Face Recognition

no code implementations ICCV 2019 Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen, Boyu Lu, Carlos D. Castillo, Rama Chellappa

In this paper, we propose the Uncertainty-Gated Graph (UGG), which conducts graph-based identity propagation between tracklets, which are represented by nodes in a graph.

Face Recognition

Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN

2 code implementations CVPR 2019 Shiyi Lan, Ruichi Yu, Gang Yu, Larry S. Davis

This encourages the network to preserve the geometric structure in Euclidean space throughout the feature extraction hierarchy.

Modeling Local Geometric Structure

Layout-induced Video Representation for Recognizing Agent-in-Place Actions

no code implementations ICCV 2019 Ruichi Yu, Hongcheng Wang, Ang Li, Jingxiao Zheng, Vlad I. Morariu, Larry S. Davis

We address the recognition of agent-in-place actions, which are associated with agents who perform them and places where they occur, in the context of outdoor home surveillance.

ReMotENet: Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos

no code implementations6 Jan 2018 Ruichi Yu, Hongcheng Wang, Larry S. Davis

To dramatically speedup relevant motion event detection and improve its performance, we propose a novel network for relevant motion event detection, ReMotENet, which is a unified, end-to-end data-driven method using spatial-temporal attention-based 3D ConvNets to jointly model the appearance and motion of objects-of-interest in a video.

Event Detection Object Detection

VITON: An Image-based Virtual Try-on Network

5 code implementations CVPR 2018 Xintong Han, Zuxuan Wu, Zhe Wu, Ruichi Yu, Larry S. Davis

We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy.

Virtual Try-on

NISP: Pruning Networks using Neuron Importance Score Propagation

no code implementations CVPR 2018 Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I. Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, Larry S. Davis

In contrast, we argue that it is essential to prune neurons in the entire neuron network jointly based on a unified goal: minimizing the reconstruction error of important responses in the "final response layer" (FRL), which is the second-to-last layer before classification, for a pruned network to retrain its predictive power.

Network Pruning

C-WSL: Count-guided Weakly Supervised Localization

no code implementations ECCV 2018 Mingfei Gao, Ang Li, Ruichi Yu, Vlad I. Morariu, Larry S. Davis

We introduce count-guided weakly supervised localization (C-WSL), an approach that uses per-class object count as a new form of supervision to improve weakly supervised localization (WSL).

Dynamic Zoom-in Network for Fast Object Detection in Large Images

no code implementations CVPR 2018 Mingfei Gao, Ruichi Yu, Ang Li, Vlad I. Morariu, Larry S. Davis

We introduce a generic framework that reduces the computational cost of object detection while retaining accuracy for scenarios where objects with varied sizes appear in high resolution images.

Real-Time Object Detection

Generating Holistic 3D Scene Abstractions for Text-based Image Retrieval

no code implementations CVPR 2017 Ang Li, Jin Sun, Joe Yue-Hei Ng, Ruichi Yu, Vlad I. Morariu, Larry S. Davis

Since interactions between objects can be reduced to a limited set of atomic spatial relations in 3D, we study the possibility of inferring 3D structure from a text description rather than an image, applying physical relation models to synthesize holistic 3D abstract object layouts satisfying the spatial constraints present in a textual description.

Image Retrieval Object Detection

The Role of Context Selection in Object Detection

no code implementations9 Sep 2016 Ruichi Yu, Xi Chen, Vlad I. Morariu, Larry S. Davis

We investigate the reasons why context in object detection has limited utility by isolating and evaluating the predictive power of different context cues under ideal conditions in which context provided by an oracle.

Object Detection

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