Search Results for author: Guanhang Wu

Found 11 papers, 5 papers with code

TDT: Teaching Detectors to Track without Fully Annotated Videos

no code implementations11 May 2022 Shuzhi Yu, Guanhang Wu, Chunhui Gu, Mohammed E. Fathy

However, their success depends on the availability of videos that are fully annotated with tracking data, which is expensive and hard to obtain.

Multi-Object Tracking

The Auto Arborist Dataset: A Large-Scale Benchmark for Multiview Urban Forest Monitoring Under Domain Shift

no code implementations CVPR 2022 Sara Beery, Guanhang Wu, Trevor Edwards, Filip Pavetic, Bo Majewski, Shreyasee Mukherjee, Stanley Chan, John Morgan, Vivek Rathod, Jonathan Huang

We introduce baseline results on our dataset across modalities as well as metrics for the detailed analysis of generalization with respect to geographic distribution shifts, vital for such a system to be deployed at-scale.

Management

Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts

no code implementations11 Jan 2021 Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister

To address this issue, we introduce a new method for pre-training video action recognition models using queried web videos.

Action Recognition pseudo label

Exploring Sub-Pseudo Labels for Learning from Weakly-Labeled Web Videos

no code implementations1 Jan 2021 Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Yun Fu, Tomas Pfister

To address this issue, we introduce a new method for pre-training video action recognition models using queried web videos.

Action Recognition pseudo label

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

3 code implementations CVPR 2020 Sara Beery, Guanhang Wu, Vivek Rathod, Ronny Votel, Jonathan Huang

In this paper we propose a method that leverages temporal context from the unlabeled frames of a novel camera to improve performance at that camera.

object-detection Video Object Detection +1

Adversarial Multiple Source Domain Adaptation

no code implementations NeurIPS 2018 Han Zhao, Shanghang Zhang, Guanhang Wu, José M. F. Moura, Joao P. Costeira, Geoffrey J. Gordon

In this paper we propose new generalization bounds and algorithms under both classification and regression settings for unsupervised multiple source domain adaptation.

Classification Domain Adaptation +4

Multiple Source Domain Adaptation with Adversarial Learning

no code implementations ICLR 2018 Han Zhao, Shanghang Zhang, Guanhang Wu, Jo\~{a}o P. Costeira, Jos\'{e} M. F. Moura, Geoffrey J. Gordon

We propose a new generalization bound for domain adaptation when there are multiple source domains with labeled instances and one target domain with unlabeled instances.

Domain Adaptation Sentiment Analysis

Topology Adaptive Graph Convolutional Networks

2 code implementations ICLR 2018 Jian Du, Shanghang Zhang, Guanhang Wu, Jose M. F. Moura, Soummya Kar

Spectral graph convolutional neural networks (CNNs) require approximation to the convolution to alleviate the computational complexity, resulting in performance loss.

FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras

1 code implementation ICCV 2017 Shanghang Zhang, Guanhang Wu, João P. Costeira, José M. F. Moura

To overcome limitations of existing methods and incorporate the temporal information of traffic video, we design a novel FCN-rLSTM network to jointly estimate vehicle density and vehicle count by connecting fully convolutional neural networks (FCN) with long short term memory networks (LSTM) in a residual learning fashion.

Multiple Source Domain Adaptation with Adversarial Training of Neural Networks

4 code implementations26 May 2017 Han Zhao, Shanghang Zhang, Guanhang Wu, João P. Costeira, José M. F. Moura, Geoffrey J. Gordon

As a step toward bridging the gap, we propose a new generalization bound for domain adaptation when there are multiple source domains with labeled instances and one target domain with unlabeled instances.

Domain Adaptation Sentiment Analysis

Understanding Traffic Density from Large-Scale Web Camera Data

1 code implementation CVPR 2017 Shanghang Zhang, Guanhang Wu, João P. Costeira, José M. F. Moura

Understanding traffic density from large-scale web camera (webcam) videos is a challenging problem because such videos have low spatial and temporal resolution, high occlusion and large perspective.

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