Alexander G. Schwing

发表

Asynchronous Parallel Coordinate Minimization for MAP Inference

Ofer Meshi, Alexander G. Schwing, 2017, NIPS.

Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering

Svetlana Lazebnik, Alexander G. Schwing, Medhini Narasimhan, 2018, NeurIPS.

Max-Sliced Wasserstein Distance and Its Use for GANs

David A. Forsyth, Zhizhen Zhao, Oluwasanmi Koyejo, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

High-Order Attention Models for Visual Question Answering

Tamir Hazan, Alexander G. Schwing, Idan Schwartz, 2017, NIPS.

Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials

Raquel Urtasun, Shenlong Wang, Alexander G. Schwing, 2014, NIPS.

A Simple Baseline for Audio-Visual Scene-Aware Dialog

Tamir Hazan, Alexander G. Schwing, Idan Schwartz, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Efficient Deep Learning for Stereo Matching

Raquel Urtasun, Alexander G. Schwing, Wenjie Luo, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space

Svetlana Lazebnik, Alexander G. Schwing, Liwei Wang, 2017, NIPS.

Enabling real-time multi-messenger astrophysics discoveries with deep learning pdf

Hongyu Shen, E. A. Huerta, Francisco Förster, 2019, Nature Reviews Physics.

Structural Consistency and Controllability for Diverse Colorization pdf

David A. Forsyth, Alexander G. Schwing, Safa Messaoud, 2018, ECCV.

Design of Single-Group Multicasting-Beamformers

Wolfgang Utschick, David A. Schmidt, Alexander G. Schwing, 2007, 2007 IEEE International Conference on Communications.

Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening pdf

Yang Liu, Jian Peng, Alexander G. Schwing, 2016, ICLR.

Learning to segment under various forms of weak supervision

Jia Xu, Raquel Urtasun, Alexander G. Schwing, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Message Passing Inference for Large Scale Graphical Models with High Order Potentials

Jian Zhang, Raquel Urtasun, Alexander G. Schwing, 2014, NIPS.

PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

Alexander G. Schwing, Raymond A. Yeh, Iou-Jen Liu, 2019, CoRL.

Semantic Image Inpainting with Deep Generative Models

Minh N. Do, Mark Hasegawa-Johnson, Alexander G. Schwing, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Latent Structured Active Learning

Raquel Urtasun, Alexander G. Schwing, Wenjie Luo, 2013, NIPS.

Two Body Problem: Collaborative Visual Task Completion

Ali Farhadi, Svetlana Lazebnik, Alexander G. Schwing, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Image Restoration with Deep Generative Models

Minh N. Do, Mark Hasegawa-Johnson, Alexander G. Schwing, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

An Elevator Pitch on Deep Learning

Alexander G. Schwing, Yuan-Ting Hu, 2017, GETMBL.

Distributed Estimation via Opinion Dynamics

Andrew C. Singer, Alexander G. Schwing, Noyan C. Sevüktekin, 2019, 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS).

Co-Generation with GANs using AIS based HMC

Alexander G. Schwing, Tiantian Fang, A. Schwing, 2019, NeurIPS.

Efficient Structured Prediction with Latent Variables for General Graphical Models

Marc Pollefeys, Tamir Hazan, Raquel Urtasun, 2012, ICML.

Deep Structured Prediction with Nonlinear Output Transformations

Ofer Meshi, Alexander G. Schwing, Colin Graber, 2018, NeurIPS.

Rent3D: Floor-plan priors for monocular layout estimation

Sanja Fidler, Chenxi Liu, Raquel Urtasun, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Accelerating Distributed Reinforcement learning with In-Switch Computing

Alexander G. Schwing, Deming Chen, Jian Huang, 2019, 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA).

Pose Estimation of a Camera using Newton Optimization on the Manifold

Klaus Diepold, Alexander G. Schwing, Michel Sarkis, 2008 .

Fully automatic segmentation of wrist bones for arthritis patients

Marc Pollefeys, Dorin Comaniciu, Alexander G. Schwing, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

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

Jan Kautz, Alexander G. Schwing, Ming-Yu Liu, 2020, ECCV.

SAIL-VOS: Semantic Amodal Instance Level Video Object Segmentation – A Synthetic Dataset and Baselines

Alexander G. Schwing, Jia-Bin Huang, Yuan-Ting Hu, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training

Nam Sung Kim, Alexander G. Schwing, Amir Salman Avestimehr, 2018, NeurIPS.

Match Box: Indoor Image Matching via Box-Like Scene Estimation

Marc Pollefeys, Tomás Pajdla, Alexander G. Schwing, 2014, 2014 2nd International Conference on 3D Vision.

Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors

Jian Zhang, Raquel Urtasun, Alexander G. Schwing, 2013, 2013 IEEE International Conference on Computer Vision.

Diverse and Controllable Image Captioning with Part-of-Speech Guidance pdf

David A. Forsyth, Alexander G. Schwing, Liwei Wang, 2018, ArXiv.

Smooth and Strong: MAP Inference with Linear Convergence

Ofer Meshi, Alexander G. Schwing, Mehrdad Mahdavi, 2015, NIPS.

Knowledge Flow: Improve Upon Your Teachers pdf

Jian Peng, Alexander G. Schwing, Iou-Jen Liu, 2019, ICLR.

Computational Education using Latent Structured Prediction

Markus H. Gross, Tamir Hazan, Alexander G. Schwing, 2014, AISTATS.

Can We Learn Heuristics for Graphical Model Inference Using Reinforcement Learning?

Alexander G. Schwing, Maghav Kumar, Safa Messaoud, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Efficient Structured Parsing of Facades Using Dynamic Programming

Marc Pollefeys, Alexander G. Schwing, Andrea Cohen, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Chirality Nets for Human Pose Regression

Alexander G. Schwing, Yuan-Ting Hu, Raymond A. Yeh, 2019, NeurIPS.

Adaptive random forest — How many “experts” to ask before making a decision?

Marc Pollefeys, Alexander G. Schwing, Yefeng Zheng, 2011, CVPR 2011.

Fast and Accurate Text Classification: Skimming, Rereading and Early Stopping

Yang Liu, Jian Peng, Alexander G. Schwing, 2018, ICLR.

Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts

Jinjun Xiong, Minh N. Do, Alexander G. Schwing, 2018, NIPS.

Learning Deep Structured Models

Alan L. Yuille, Raquel Urtasun, Alexander G. Schwing, 2014, ICML.

Tell Me What You See and I Will Show You Where It Is

Jia Xu, Raquel Urtasun, Alexander G. Schwing, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning pdf

Alexander G. Schwing, Raymond A. Yeh, Zhongzheng Ren, 2020, NeurIPS.

Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?

Alexander G. Schwing, Maghav Kumar, Safa Messaoud, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

No-Frills Human-Object Interaction Detection: Factorization, Appearance and Layout Encodings, and Training Techniques pdf

Derek Hoiem, Alexander G. Schwing, Tanmay Gupta, 2018, ArXiv.

Learning Deep Parsimonious Representations

Renjie Liao, Raquel Urtasun, Richard S. Zemel, 2016, NIPS.

Diverse and Coherent Paragraph Generation from Images

Alexander G. Schwing, Moitreya Chatterjee, A. Schwing, 2018, ECCV.

Dualing GANs

Richard S. Zemel, Yujia Li, Alexander G. Schwing, 2017, NIPS.

Graph Structured Prediction Energy Networks

Alexander G. Schwing, Colin Graber, A. Schwing, 2019, NeurIPS.

TAB-VCR: Tags and Attributes based VCR Baselines

Alexander G. Schwing, Unnat Jain, Jingxiang Lin, 2019, NeurIPS.

Constraints Based Convex Belief Propagation

Tamir Hazan, Alexander G. Schwing, Kevin Gimpel, 2016, NIPS.

Two Can Play This Game: Visual Dialog with Discriminative Question Generation and Answering

Svetlana Lazebnik, Alexander G. Schwing, Unnat Jain, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Statistical Inference, Learning and Models in Big Data pdf

Ribana Roscher, Alexander G. Schwing, Roger B. Grosse, 2015, ArXiv.

FMRI Data Augmentation Via Synthesis

Alexander G. Schwing, Peiye Zhuang, Oluwasanmi Koyejo, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Factor Graph Attention

Tamir Hazan, Alexander G. Schwing, Seunghak Yu, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm

Marc Pollefeys, Tamir Hazan, Raquel Urtasun, 2014, ICML.

Creativity: Generating Diverse Questions Using Variational Autoencoders

Alexander G. Schwing, Unnat Jain, Ziyu Zhang, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Monocular Object Instance Segmentation and Depth Ordering with CNNs

Sanja Fidler, Raquel Urtasun, Alexander G. Schwing, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training

Nam Sung Kim, Alexander G. Schwing, Amir Salman Avestimehr, 2018, NeurIPS.

VideoMatch: Matching based Video Object Segmentation pdf

Alexander G. Schwing, Jia-Bin Huang, Yuan-Ting Hu, 2018, ECCV.

Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins

Marc Pollefeys, Tamir Hazan, Raquel Urtasun, 2012, NIPS.

Generative Modeling Using the Sliced Wasserstein Distance

Alexander G. Schwing, Ishan Deshpande, Ziyu Zhang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Box in the Box: Joint 3D Layout and Object Reasoning from Single Images

Sanja Fidler, Marc Pollefeys, Raquel Urtasun, 2013, 2013 IEEE International Conference on Computer Vision.

Dynamic Bayesian Networks for Student Modeling

Alexander G. Schwing, Severin Klingler, Markus Gross, 2017, IEEE Transactions on Learning Technologies.

Enhancing the motion estimate in bundle adjustment using projective Newton-type optimization on the manifold

Klaus Diepold, Alexander G. Schwing, Michel Sarkis, 2009, Electronic Imaging.

Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering pdf

Alexander G. Schwing, Medhini Narasimhan, A. Schwing, 2018, ECCV.

Training Deep Neural Networks via Direct Loss Minimization

Yang Song, Raquel Urtasun, Richard S. Zemel, 2015, ICML.

A Simple Baseline for Visual Commonsense Reasoning

Alexander G. Schwing, Unnat Jain, Jingxiang Lin, 2019, ViGIL@NeurIPS.

Convolutional Image Captioning

Alexander G. Schwing, Aditya Deshpande, Jyoti Aneja, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era pdf

Xin Liu, Daniel George, Daniel S. Katz, 2019, ArXiv.

Blending Learning and Inference in Conditional Random Fields

Tamir Hazan, Raquel Urtasun, Alexander G. Schwing, 2016, J. Mach. Learn. Res..

Reliable extraction of the mid-sagittal plane in 3D brain MRI via hierarchical landmark detection

Alexander G. Schwing, Yefeng Zheng, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Efficient Exact Inference for 3D Indoor Scene Understanding

Raquel Urtasun, Alexander G. Schwing, A. Schwing, 2012, ECCV.

Fully Connected Deep Structured Networks pdf

Raquel Urtasun, Alexander G. Schwing, A. Schwing, 2015, ArXiv.

Direct Loss Minimization for Training Deep Neural Nets pdf

Yang Song, Raquel Urtasun, Richard S. Zemel, 2015, ArXiv.

Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation

Alexander G. Schwing, Jia-Bin Huang, Yuan-Ting Hu, 2018, ECCV.

Efficient structured prediction for 3D indoor scene understanding

Marc Pollefeys, Tamir Hazan, Raquel Urtasun, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Beyond Knowledge Tracing: Modeling Skill Topologies with Bayesian Networks

Markus H. Gross, Alexander G. Schwing, Severin Klingler, 2014, Intelligent Tutoring Systems.

PAC-Bayesian Neural Network Bounds

Tamir Hazan, Alexander G. Schwing, Yossi Adi, 2019 .

High-Throughput Synchronous Deep RL pdf

Alexander G. Schwing, Raymond A. Yeh, Iou-Jen Liu, 2020, NeurIPS.

A Network-Centric Hardware/Algorithm Co-Design to Accelerate Distributed Training of Deep Neural Networks

Mohammad Alian, Nam Sung Kim, Alexander G. Schwing, 2018, 2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

Distributed message passing for large scale graphical models

Marc Pollefeys, Tamir Hazan, Raquel Urtasun, 2011, CVPR 2011.

Unsupervised Textual Grounding: Linking Words to Image Concepts

Minh N. Do, Alexander G. Schwing, Raymond A. Yeh, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Diverse Generation for Multi-Agent Sports Games

Alexander G. Schwing, Kevin Murphy, Jonathan Huang, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Proposal-Based Video Completion

Alexander G. Schwing, Kristen Grauman, Nicolas Ballas, 2020, ECCV.

Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection

Yong Jae Lee, Jan Kautz, Alexander G. Schwing, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

MaskRNN: Instance Level Video Object Segmentation

Alexander G. Schwing, Jia-Bin Huang, Yuan-Ting Hu, 2018, NIPS.

Class-agnostic Reconstruction of Dynamic Objects from Videos pdf

Alexander G. Schwing, Zhongzheng Ren, Xiaoming Zhao, 2021, NeurIPS.

Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning

Alexander G. Schwing, Raymond A. Yeh, Iou-Jen Liu, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

FuseRec: fusing user and item homophily modeling with temporal recommender systems

Alexander G. Schwing, Hari Sundaram, Kanika Narang, 2021, Data Min. Knowl. Discov..

Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation pdf

Oluwasanmi Koyejo, Alexander G. Schwing, Peiye Zhuang, 2021, ICLR.

Masked-attention Mask Transformer for Universal Image Segmentation pdf

Alexander G. Schwing, Rohit Girdhar, Alexander Kirillov, 2021, ArXiv.

Mask2Former for Video Instance Segmentation pdf

Alexander G. Schwing, Rohit Girdhar, Alexander Kirillov, 2021, ArXiv.

Cooperative Exploration for Multi-Agent Deep Reinforcement Learning

Alexander G. Schwing, Unnat Jain, Raymond A. Yeh, 2021, ICML.

3D Spatial Recognition without Spatially Labeled 3D

Alexander G. Schwing, Rohit Girdhar, Ishan Misra, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data

Alexander G. Schwing, Yuan-Ting Hu, Raymond A. Yeh, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models

Naresh R. Shanbhag, Alexander G. Schwing, Ameya D. Patil, 2021 .

Per-Pixel Classification is Not All You Need for Semantic Segmentation pdf

Alexander G. Schwing, Alexander Kirillov, Bowen Cheng, 2021, NeurIPS.

DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization

Zhizhen Zhao, Alexander G. Schwing, Ismini Lourentzou, 2021, SIGIR.

Distributed Structured Prediction for Big Data

Marc Pollefeys, Tamir Hazan, Alexander G. Schwing, 2012 .

Multiphase flow in porous rock imaged under dynamic flow conditions with fast X-Ray computed microtomography

Alexander G. Schwing, Frieder Enzmann, Marco Stampanoni, 2014 .

From connected pathway flow to ganglion dynamics

Alexander G. Schwing, Frieder Enzmann, Ryan T. Armstrong, 2015 .

Generative Adversarial Structured Networks

Alexander G. Schwing, Ben London, A. Schwing, 2016 .

Onset of Oil Mobilization and Nonwetting-Phase Cluster-Size Distribution

Alexander G. Schwing, Frieder Enzmann, Ryan T. Armstrong, 2015 .