Alan Yuille

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Johns Hopkins University

Research Program Manager at Johns Hopkins University

Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping

Catastrophic forgetting in neural networks is a significant problem for ...
02/22/2021 ∙ by Prakhar Kaushik, et al. ∙ 0 ∙ share

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CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning

Semi-supervised learning on class-imbalanced data, although a realistic ...
02/18/2021 ∙ by Chen Wei, et al. ∙ 0 ∙ share

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Occluded Video Instance Segmentation

Can our video understanding systems perceive objects when a heavy occlus...
02/02/2021 ∙ by Jiyang Qi, et al. ∙ 12 ∙ share

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NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation

3D pose estimation is a challenging but important task in computer visio...
01/29/2021 ∙ by Angtian Wang, et al. ∙ 14 ∙ share

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COMPAS: Representation Learning with Compositional Part Sharing for Few-Shot Classification

Few-shot image classification consists of two consecutive learning proce...
01/28/2021 ∙ by Ju He, et al. ∙ 0 ∙ share

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Meticulous Object Segmentation

Compared with common image segmentation tasks targeted at low-resolution...
12/13/2020 ∙ by Chenglin Yang, et al. ∙ 0 ∙ share

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Mask Guided Matting via Progressive Refinement Network

We propose Mask Guided (MG) Matting, a robust matting framework that tak...
12/12/2020 ∙ by Qihang Yu, et al. ∙ 0 ∙ share

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ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation

In this paper, we present ViP-DeepLab, a unified model attempting to tac...
12/09/2020 ∙ by Siyuan Qiao, et al. ∙ 3 ∙ share

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Robust Instance Segmentation through Reasoning about Multi-Object Occlusion

Analyzing complex scenes with Deep Neural Networks is a challenging task...
12/03/2020 ∙ by Xiaoding Yuan, et al. ∙ 9 ∙ share

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MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers

We present MaX-DeepLab, the first end-to-end model for panoptic segmenta...
12/01/2020 ∙ by Huiyu Wang, et al. ∙ 0 ∙ share

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Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks

Patch-based adversarial attacks introduce a perceptible but localized ch...
12/01/2020 ∙ by Christian Cosgrove, et al. ∙ 0 ∙ share

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Unsupervised Part Discovery via Feature Alignment

Understanding objects in terms of their individual parts is important, b...
12/01/2020 ∙ by Mengqi Guo, et al. ∙ 7 ∙ share

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Batch Normalization with Enhanced Linear Transformation

Batch normalization (BN) is a fundamental unit in modern deep networks, ...
11/28/2020 ∙ by Yuhui Xu, et al. ∙ 15 ∙ share

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Can Temporal Information Help with Contrastive Self-Supervised Learning?

Leveraging temporal information has been regarded as essential for devel...
11/25/2020 ∙ by Yutong Bai, et al. ∙ 10 ∙ share

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Weakly-Supervised Amodal Instance Segmentation with Compositional Priors

Amodal segmentation in biological vision refers to the perception of the...
10/25/2020 ∙ by Yihong Sun, et al. ∙ 0 ∙ share

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Shape-Texture Debiased Neural Network Training

Shape and texture are two prominent and complementary cues for recognizi...
10/12/2020 ∙ by Yingwei Li, et al. ∙ 21 ∙ share

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CO2: Consistent Contrast for Unsupervised Visual Representation Learning

Contrastive learning has been adopted as a core method for unsupervised ...
10/05/2020 ∙ by Chen Wei, et al. ∙ 9 ∙ share

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CoKe: Localized Contrastive Learning for Robust Keypoint Detection

Today's most popular approaches to keypoint detection learn a holistic r...
09/29/2020 ∙ by Yutong Bai, et al. ∙ 8 ∙ share

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Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

Determining the spread of GTV_LN is essential in defining the respective...
08/29/2020 ∙ by Chun-Hung Chao, et al. ∙ 9 ∙ share

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Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy

Finding, identifying and segmenting suspicious cancer metastasized lymph...
08/27/2020 ∙ by Zhuotun Zhu, et al. ∙ 5 ∙ share

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ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

Recent works of point clouds show that mulit-frame spatio-temporal model...
08/12/2020 ∙ by Hanwen Cao, et al. ∙ 4 ∙ share

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Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles

Trajectory prediction is crucial for autonomous vehicles. The planning s...
07/06/2020 ∙ by Chenxu Luo, et al. ∙ 4 ∙ 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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Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion

Computer vision systems in real-world applications need to be robust to ...
06/28/2020 ∙ by Adam Kortylewski, et al. ∙ 0 ∙ share

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Smooth Adversarial Training

It is commonly believed that networks cannot be both accurate and robust...
06/25/2020 ∙ by Cihang Xie, et al. ∙ 13 ∙ share

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DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

Many modern object detectors demonstrate outstanding performances by usi...
06/03/2020 ∙ by Siyuan Qiao, et al. ∙ 0 ∙ share

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Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification

Finding and identifying scatteredly-distributed, small, and critically i...
05/27/2020 ∙ by Zhuotun Zhu, et al. ∙ 4 ∙ share

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Robust Object Detection under Occlusion with Context-Aware CompositionalNets

Detecting partially occluded objects is a difficult task. Our experiment...
05/24/2020 ∙ by Angtian Wang, et al. ∙ 16 ∙ share

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Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation

In this paper, we present a novel unsupervised domain adaptation (UDA) m...
05/18/2020 ∙ by Shuhao Fu, et al. ∙ 6 ∙ share

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Organ at Risk Segmentation for Head and Neck Cancer using Stratified Learning and Neural Architecture Search

OAR segmentation is a critical step in radiotherapy of head and neck (H ...
04/17/2020 ∙ by Dazhou Guo, et al. ∙ 6 ∙ share

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PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning

Patch-based attacks introduce a perceptible but localized change to the ...
04/12/2020 ∙ by Chenglin Yang, et al. ∙ 6 ∙ share

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Context-Aware Group Captioning via Self-Attention and Contrastive Features

While image captioning has progressed rapidly, existing works focus main...
04/07/2020 ∙ by Zhuowan Li, et al. ∙ 1 ∙ share

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Neural Architecture Search for Lightweight Non-Local Networks

Non-Local (NL) blocks have been widely studied in various vision tasks. ...
04/04/2020 ∙ by Yingwei Li, et al. ∙ 5 ∙ share

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Are Labels Necessary for Neural Architecture Search?

Existing neural network architectures in computer vision — whether desig...
03/26/2020 ∙ by Chenxi Liu, et al. ∙ 14 ∙ share

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Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation

The ability to detect failures and anomalies are fundamental requirement...
03/18/2020 ∙ by Yingda Xia, et al. ∙ 6 ∙ share

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Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Convolution exploits locality for efficiency at a cost of missing long r...
03/17/2020 ∙ by Huiyu Wang, et al. ∙ 8 ∙ share

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Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion

Recent work has shown that deep convolutional neural networks (DCNNs) do...
03/10/2020 ∙ by Adam Kortylewski, et al. ∙ 0 ∙ share

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When Radiology Report Generation Meets Knowledge Graph

Automatic radiology report generation has been an attracting research pr...
02/19/2020 ∙ by Yixiao Zhang, et al. ∙ 0 ∙ share

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Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots

Accurate 3D object detection in LiDAR based point clouds suffers from th...
12/30/2019 ∙ by Qi Chen, et al. ∙ 7 ∙ share

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AtomNAS: Fine-Grained End-to-End Neural Architecture Search

Designing of search space is a critical problem for neural architecture ...
12/20/2019 ∙ by Jieru Mei, et al. ∙ 16 ∙ share

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Learning from Synthetic Animals

Despite great success in human parsing, progress for parsing other defor...
12/17/2019 ∙ by Jiteng Mu, et al. ∙ 19 ∙ share

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Identity Preserve Transform: Understand What Activity Classification Models Have Learnt

Activity classification has observed great success recently. The perform...
12/13/2019 ∙ by Jialing Lyu, et al. ∙ 7 ∙ share

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Zero-shot Recognition of Complex Action Sequences

Zero-shot video classification for fine-grained activity recognition has...
12/08/2019 ∙ by Jonathan D. Jones, et al. ∙ 0 ∙ share

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RSA: Randomized Simulation as Augmentation for Robust Human Action Recognition

Despite the rapid growth in datasets for video activity, stable robust a...
12/03/2019 ∙ by Yi Zhang, et al. ∙ 8 ∙ share

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Shape-aware Feature Extraction for Instance Segmentation

Modern instance segmentation approaches mainly adopt a sequential paradi...
11/25/2019 ∙ by Hao Ding, et al. ∙ 0 ∙ share

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Identifying Model Weakness with Adversarial Examiner

Machine learning models are usually evaluated according to the average c...
11/25/2019 ∙ by Michelle Shu, et al. ∙ 0 ∙ share

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Rethinking Normalization and Elimination Singularity in Neural Networks

In this paper, we study normalization methods for neural networks from t...
11/21/2019 ∙ by Siyuan Qiao, et al. ∙ 0 ∙ share

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Adversarial Examples Improve Image Recognition

Adversarial examples are commonly viewed as a threat to ConvNets. Here w...
11/21/2019 ∙ by Cihang Xie, et al. ∙ 24 ∙ share

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Localizing Occluders with Compositional Convolutional Networks

Compositional convolutional networks are generative compositional models...
11/18/2019 ∙ by Adam Kortylewski, et al. ∙ 0 ∙ share

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Grouped Spatial-Temporal Aggregation for Efficient Action Recognition

Temporal reasoning is an important aspect of video analysis. 3D CNN show...
09/28/2019 ∙ by Chenxu Luo, et al. ∙ 0 ∙ share

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Alan Yuille

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