10.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS1.5k papers
- Michigan State UniversityUS1.5k papers
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- Lawrence Berkeley National LaboratoryUS1.4k papers
- McGill UniversityCA1.4k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR1.3k papers
- University of ManchesterGB1.3k papers
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19 papers · 2 filters
Batch DropBlock Network for Person Re-identification and Beyond
Zuozhuo Dai, Mingqiang Chen, Xiaodong Gu +2
Since the person re-identification task often suffers from the problem of pose changes and occlusions, some attentive local features are often suppressed when training CNNs. In thi…
Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with Deep Classification Features
Philipp Tschandl, Giuseppe Argenziano, Majid Razmara +1
Background: Automated classification of medical images through neural networks can reach high accuracy rates but lack interpretability. Objectives: To compare the diagnostic accura…
Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction
Yatao Zhong, Bicheng Xu, Guang-Tong Zhou +2
Numerous powerful point process models have been developed to understand temporal patterns in sequential data from fields such as health-care, electronic commerce, social networks,…
SketchyScene: Richly-Annotated Scene Sketches
Changqing Zou, Qian Yu, Ruofei Du +6
We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dat…
Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks
Saeid Asgari Taghanaki, Arkadeep Das, Ghassan Hamarneh
Recently, there have been several successful deep learning approaches for automatically classifying chest X-ray images into different disease categories. However, there is not yet…
Star Shape Prior in Fully Convolutional Networks for Skin Lesion Segmentation
Zahra Mirikharaji, Ghassan Hamarneh
Semantic segmentation is an important preliminary step towards automatic medical image interpretation. Recently deep convolutional neural networks have become the first choice for…
Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?
Saeed Izadi, Kathleen P. Moriarty, Ghassan Hamarneh
Confocal laser endomicroscopy (CLE) is a novel imaging modality that provides in vivo histological cross-sections of examined tissue. Recently, attempts have been made to develop m…
Object Level Visual Reasoning in Videos
Fabien Baradel, Natalia Neverova, Christian Wolf +2
Human activity recognition is typically addressed by detecting key concepts like global and local motion, features related to object classes present in the scene, as well as featur…
BA-Net: Dense Bundle Adjustment Network
Chengzhou Tang, Ping Tan
This paper introduces a network architecture to solve the structure-from-motion (SfM) problem via feature-metric bundle adjustment (BA), which explicitly enforces multi-view geomet…
DSSLIC: Deep Semantic Segmentation-based Layered Image Compression
Mohammad Akbari, Jie Liang, Jingning Han
Deep learning has revolutionized many computer vision fields in the last few years, including learning-based image compression. In this paper, we propose a deep semantic segmentati…
Rehabilitating the ColorChecker Dataset for Illuminant Estimation
Ghalia Hemrit, Graham D. Finlayson, Arjan Gijsenij +5
In a previous work, it was shown that there is a curious problem with the benchmark ColorChecker dataset for illuminant estimation. To wit, this dataset has at least 3 different se…
PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image
Chen Liu, Jimei Yang, Duygu Ceylan +2
This paper proposes a deep neural network (DNN) for piece-wise planar depthmap reconstruction from a single RGB image. While DNNs have brought remarkable progress to single-image d…
Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings
Kevin Chen, Christopher B. Choy, Manolis Savva +3
We present a method for generating colored 3D shapes from natural language. To this end, we first learn joint embeddings of freeform text descriptions and colored 3D shapes. Our mo…
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis
Zili Yi, Zhiqin Chen, Hao Cai +3
We introduce BSD-GAN, a novel multi-branch and scale-disentangled training method which enables unconditional Generative Adversarial Networks (GANs) to learn image representations…
Faces as Lighting Probes via Unsupervised Deep Highlight Extraction
Renjiao Yi, Chenyang Zhu, Ping Tan +1
We present a method for estimating detailed scene illumination using human faces in a single image. In contrast to previous works that estimate lighting in terms of low-order basis…
On the Applicability of Registration Uncertainty
Jie Luo, Alireza Sedghi, Karteek Popuri +8
Estimating the uncertainty in (probabilistic) image registration enables, e.g., surgeons to assess the operative risk based on the trustworthiness of the registered image data. If…
Structured Label Inference for Visual Understanding
Nelson Nauata, Hexiang Hu, Guang-Tong Zhou +3
Visual data such as images and videos contain a rich source of structured semantic labels as well as a wide range of interacting components. Visual content could be assigned with f…
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
Lingyang Chu, Xia Hu, Juhua Hu +2
Strong intelligent machines powered by deep neural networks are increasingly deployed as black boxes to make decisions in risk-sensitive domains, such as finance and medical. To re…
Sparsely Aggregated Convolutional Networks
Ligeng Zhu, Ruizhi Deng, Michael Maire +3
We explore a key architectural aspect of deep convolutional neural networks: the pattern of internal skip connections used to aggregate outputs of earlier layers for consumption by…