b'Zhiding Yu'

Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection

Training on datasets with long-tailed distributions has been challenging...
04/12/2021 ∙ by Nadine Chang, et al. ∙ 27 ∙ share

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Contrastive Syn-to-Real Generalization

Training on synthetic data can be beneficial for label or data-scarce sc...
04/06/2021 ∙ by Wuyang Chen, et al. ∙ 7 ∙ share

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UFO^2: A Unified Framework towards Omni-supervised Object Detection

Existing work on object detection often relies on a single form of annot...
10/21/2020 ∙ by Zhongzheng Ren, et al. ∙ 0 ∙ share

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Distributionally Robust Learning for Unsupervised Domain Adaptation

We propose a distributionally robust learning (DRL) method for unsupervi...
10/08/2020 ∙ by Haoxuan Wang, et al. ∙ 2 ∙ share

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Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning

Humans have an inherent ability to learn novel concepts from only a few ...
10/02/2020 ∙ by Weili Nie, et al. ∙ 10 ∙ share

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Delving Deeper into Anti-aliasing in ConvNets

Aliasing refers to the phenomenon that high frequency signals degenerate...
08/21/2020 ∙ by Xueyan Zou, et al. ∙ 41 ∙ share

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Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification

Although a significant progress has been witnessed in supervised person ...
07/20/2020 ∙ by Yang Zou, et al. ∙ 11 ∙ share

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Unsupervised Controllable Generation with Self-Training

Recent generative adversarial networks (GANs) are able to generate impre...
07/17/2020 ∙ by Grigorios G. Chrysos, et al. ∙ 23 ∙ share

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Neural Networks with Recurrent Generative Feedback

Neural networks are vulnerable to input perturbations such as additive n...
07/17/2020 ∙ by Yujia Huang, et al. ∙ 22 ∙ share

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Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

Conventional CNNs for texture synthesis consist of a sequence of (de)-co...
07/14/2020 ∙ by Guilin Liu, et al. ∙ 2 ∙ share

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Automated Synthetic-to-Real Generalization

Models trained on synthetic images often face degraded generalization to...
07/14/2020 ∙ by Wuyang Chen, et al. ∙ 9 ∙ share

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Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

Although having achieved great success in medical image segmentation, de...
06/28/2020 ∙ by Yingda Xia, et al. ∙ 3 ∙ share

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Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

Weakly supervised learning has emerged as a compelling tool for object d...
04/09/2020 ∙ by Zhongzheng Ren, et al. ∙ 2 ∙ share

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Angular Visual Hardness

Although convolutional neural networks (CNNs) are inspired by the mechan...
12/04/2019 ∙ by Beidi Chen, et al. ∙ 66 ∙ share

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Confidence Regularized Self-Training

Recent advances in domain adaptation show that deep self-training presen...
08/26/2019 ∙ by Yang Zou, et al. ∙ 13 ∙ share

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Compressive Hyperspherical Energy Minimization

Recent work on minimum hyperspherical energy (MHE) has demonstrated its ...
06/12/2019 ∙ by Rongmei Lin, et al. ∙ 0 ∙ share

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Joint Discriminative and Generative Learning for Person Re-identification

Person re-identification (re-id) remains challenging due to significant ...
04/15/2019 ∙ by Zhedong Zheng, et al. ∙ 20 ∙ share

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Partial Convolution based Padding

In this paper, we present a simple yet effective padding scheme that can...
11/28/2018 ∙ by Guilin Liu, et al. ∙ 6 ∙ share

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Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training

Recent deep networks achieved state of the art performance on a variety ...
10/18/2018 ∙ by Yang Zou, et al. ∙ 0 ∙ share

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Simultaneous Edge Alignment and Learning

Edge detection is among the most fundamental vision problems for its rol...
08/06/2018 ∙ by Zhiding Yu, et al. ∙ 6 ∙ share

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Learning towards Minimum Hyperspherical Energy

Neural networks are a powerful class of nonlinear functions that can be ...
05/23/2018 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Decoupled Networks

Inner product-based convolution has been a central component of convolut...
04/22/2018 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Learning Strict Identity Mappings in Deep Residual Networks

A family of super deep networks, referred to as residual networks or Res...
04/05/2018 ∙ by Xin Yu, et al. ∙ 0 ∙ share

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Deep Hyperspherical Learning

Convolution as inner product has been the founding basis of convolutiona...
11/08/2017 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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CASENet: Deep Category-Aware Semantic Edge Detection

Boundary and edge cues are highly beneficial in improving a wide variety...
05/27/2017 ∙ by Zhiding Yu, et al. ∙ 0 ∙ share

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Structured Hough Voting for Vision-based Highway Border Detection

We propose a vision-based highway border detection algorithm using struc...
11/18/2014 ∙ by Zhiding Yu, et al. ∙ 0 ∙ share

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KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization

We consider the image classification problem via kernel collaborative re...
10/17/2014 ∙ by Weiyang Liu, et al. ∙ 0 ∙ share

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Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering

Under the framework of graph-based learning, the key to robust subspace ...
09/05/2012 ∙ by Xi Peng, et al. ∙ 0 ∙ share

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Zhiding Yu

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