Leonid Sigal

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Disney Research ∙ The University of British Columbia

Associate Professor in the Department of Computer Science at the University of British Columbia, Senior Research Scientist at Disney Research Pittsburgh from 2010-2017, Adjunct Faculty member at Carnegie Mellon University, Postdoctoral Researcher at University of Toronto from 2007-2009, Summer Intern at Intel Corporation 2006

Featured Co-authors

Masashi Sugiyama
157 publications
Eric P Xing
123 publications
Kate Saenko
93 publications
Larry S. Davis
81 publications
Tao Xiang
77 publications
Yuan Yao
62 publications
Frank Wood
62 publications
Yanwei Fu
59 publications
Zhi-Hua Zhou
57 publications
Shaogang Gong
56 publications
Xiangyang Xue
53 publications

An Improved Attention for Visual Question Answering

We consider the problem of Visual Question Answering (VQA). Given an ima...
11/04/2020 ∙ by Tanzila Rahman, et al. ∙ 2 ∙ share

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Person-in-Context Synthesiswith Compositional Structural Space

Despite significant progress, controlled generation of complex images wi...
08/28/2020 ∙ by Weidong Yin, et al. ∙ 1 ∙ share

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Attribute-guided image generation from layout

Recent approaches have achieved great success in image generation from s...
08/27/2020 ∙ by Ke Ma, et al. ∙ 0 ∙ share

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Unsupervised Video Decomposition using Spatio-temporal Iterative Inference

Unsupervised multi-object scene decomposition is a fast-emerging problem...
06/25/2020 ∙ by Polina Zablotskaia, et al. ∙ 0 ∙ share

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Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment

In this study, we focus on the unsupervised domain adaptation problem wh...
06/23/2020 ∙ by Jing Wang, et al. ∙ 0 ∙ share

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Discriminative Feature Alignment: ImprovingTransferability of Unsupervised DomainAdaptation by Gaussian-guided LatentAlignment

In this study, we focus on the unsupervised domain adaptation problem wh...
06/23/2020 ∙ by Jing Wang, et al. ∙ 0 ∙ share

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Weakly-supervised Any-shot Object Detection

Methods for object detection and segmentation rely on large scale instan...
06/12/2020 ∙ by Siddhesh Khandelwal, et al. ∙ 0 ∙ share

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Consistent Multiple Sequence Decoding

Sequence decoding is one of the core components of most visual-lingual m...
04/02/2020 ∙ by Bicheng Xu, et al. ∙ 0 ∙ share

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Variational Hyper RNN for Sequence Modeling

In this work, we propose a novel probabilistic sequence model that excel...
02/24/2020 ∙ by Ruizhi Deng, et al. ∙ 23 ∙ share

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Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction

Reconstruction of a 3D shape from a single 2D image is a classical compu...
12/23/2019 ∙ by Yuan Yao, et al. ∙ 0 ∙ share

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Improved Few-Shot Visual Classification

Few-shot learning is a fundamental task in computer vision that carries ...
12/07/2019 ∙ by Peyman Bateni, et al. ∙ 1 ∙ share

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Zero-Shot Generation of Human-Object Interaction Videos

Generation of videos of complex scenes is an important open problem in c...
12/05/2019 ∙ by Megha Nawhal, et al. ∙ 9 ∙ share

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OptiBox: Breaking the Limits of Proposals for Visual Grounding

The problem of language grounding has attracted much attention in recent...
11/29/2019 ∙ by Zicong Fan, et al. ∙ 0 ∙ share

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DwNet: Dense warp-based network for pose-guided human video generation

Generation of realistic high-resolution videos of human subjects is a ch...
10/21/2019 ∙ by Polina Zablotskaia, et al. ∙ 14 ∙ share

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Watch, Listen and Tell: Multi-modal Weakly Supervised Dense Event Captioning

Multi-modal learning, particularly among imaging and linguistic modaliti...
09/22/2019 ∙ by Tanzila Rahman, et al. ∙ 0 ∙ share

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LayoutVAE: Stochastic Scene Layout Generation from a Label Set

Recently there is an increasing interest in scene generation within the ...
07/24/2019 ∙ by Akash Abdu Jyothi, et al. ∙ 3 ∙ share

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AttentionRNN: A Structured Spatial Attention Mechanism

Visual attention mechanisms have proven to be integrally important const...
05/22/2019 ∙ by Siddhesh Khandelwal, et al. ∙ 31 ∙ share

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A Variational Auto-Encoder Model for Stochastic Point Processes

We propose a novel probabilistic generative model for action sequences. ...
04/05/2019 ∙ by Nazanin Mehrasa, et al. ∙ 0 ∙ share

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Neural Sequential Phrase Grounding (SeqGROUND)

We propose an end-to-end approach for phrase grounding in images. Unlike...
03/18/2019 ∙ by Pelin Dogan, et al. ∙ 8 ∙ share

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Walking on Thin Air: Environment-Free Physics-based Markerless Motion Capture

We propose a generative approach to physics-based motion capture. Unlike...
12/04/2018 ∙ by Micha Livne, et al. ∙ 0 ∙ share

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Towards Traversing the Continuous Spectrum of Image Retrieval

Image retrieval is one of the most popular tasks in computer vision. How...
12/01/2018 ∙ by Ziad Al-Halah, et al. ∙ 0 ∙ share

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Image Generation from Layout

Despite significant recent progress on generative models, controlled gen...
11/28/2018 ∙ by Bo Zhao, et al. ∙ 0 ∙ share

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Middle-Out Decoding

Despite being virtually ubiquitous, sequence-to-sequence models are chal...
10/28/2018 ∙ by Shikib Mehri, et al. ∙ 0 ∙ share

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Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective

This paper studies the problem of domain division problem which aims to ...
10/17/2018 ∙ by HanZe Dong, et al. ∙ 0 ∙ share

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Where and When to Look? Spatio-temporal Attention for Action Recognition in Videos

Inspired by the observation that humans are able to process videos effic...
10/01/2018 ∙ by Lili Meng, et al. ∙ 0 ∙ share

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Semantic Feature Augmentation in Few-shot Learning

A fundamental problem with few-shot learning is the scarcity of data in ...
04/15/2018 ∙ by Zitian Chen, et al. ∙ 0 ∙ share

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Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning

We propose a novel method capable of retrieving clips from untrimmed vid...
04/13/2018 ∙ by Huijuan Xu, et al. ∙ 0 ∙ share

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Modular Generative Adversarial Networks

Existing methods for multi-domain image-to-image translation (or generat...
04/10/2018 ∙ by Bo Zhao, et al. ∙ 0 ∙ share

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Probabilistic Video Generation using Holistic Attribute Control

Videos express highly structured spatio-temporal patterns of visual data...
03/21/2018 ∙ by Jiawei He, et al. ∙ 2 ∙ share

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Joint Event Detection and Description in Continuous Video Streams

As a fine-grained video understanding task, dense video captioning invol...
02/28/2018 ∙ by Huijuan Xu, et al. ∙ 0 ∙ share

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LSTM stack-based Neural Multi-sequence Alignment TeCHnique (NeuMATCH)

The alignment of heterogeneous sequential data (video to text) is an imp...
02/19/2018 ∙ by Pelin Dogan, et al. ∙ 0 ∙ share

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Recent Advances in Zero-shot Recognition

With the recent renaissance of deep convolution neural networks, encoura...
10/13/2017 ∙ by Yanwei Fu, et al. ∙ 0 ∙ share

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Visual Reference Resolution using Attention Memory for Visual Dialog

Visual dialog is a task of answering a series of inter-dependent questio...
09/23/2017 ∙ by Paul Hongsuck Seo, et al. ∙ 0 ∙ share

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Predicting Personality from Book Preferences with User-Generated Content Labels

Psychological studies have shown that personality traits are associated ...
07/20/2017 ∙ by Ng Annalyn, et al. ∙ 0 ∙ share

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Weakly-supervised Visual Grounding of Phrases with Linguistic Structures

We propose a weakly-supervised approach that takes image-sentence pairs ...
05/03/2017 ∙ by Fanyi Xiao, et al. ∙ 0 ∙ share

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Weakly-Supervised Spatial Context Networks

We explore the power of spatial context as a self-supervisory signal for...
04/10/2017 ∙ by Zuxuan Wu, et al. ∙ 0 ∙ share

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Semi-Latent GAN: Learning to generate and modify facial images from attributes

Generating and manipulating human facial images using high-level attribu...
04/07/2017 ∙ by Weidong Yin, et al. ∙ 0 ∙ share

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Learning to Generate Posters of Scientific Papers by Probabilistic Graphical Models

Researchers often summarize their work in the form of scientific posters...
02/21/2017 ∙ by Yu-ting Qiang, et al. ∙ 0 ∙ share

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Learning Language-Visual Embedding for Movie Understanding with Natural-Language

Learning a joint language-visual embedding has a number of very appealin...
09/26/2016 ∙ by Atousa Torabi, et al. ∙ 0 ∙ share

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Semi-supervised Vocabulary-informed Learning

Despite significant progress in object categorization, in recent years, ...
04/24/2016 ∙ by Yanwei Fu, et al. ∙ 0 ∙ share

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Learning to Generate Posters of Scientific Papers

Researchers often summarize their work in the form of posters. Posters p...
04/05/2016 ∙ by Yuting Qiang, et al. ∙ 0 ∙ share

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Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web

Recently, attempts have been made to collect millions of videos to train...
12/22/2015 ∙ by Shugao Ma, et al. ∙ 0 ∙ share

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Robust Classification by Pre-conditioned LASSO and Transductive Diffusion Component Analysis

Modern machine learning-based recognition approaches require large-scale...
11/19/2015 ∙ by Yanwei Fu, et al. ∙ 0 ∙ share

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Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization

Emotional content is a key element in user-generated videos. However, it...
11/16/2015 ∙ by Baohan Xu, et al. ∙ 0 ∙ share

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Learning from Synthetic Data Using a Stacked Multichannel Autoencoder

Learning from synthetic data has many important and practical applicatio...
09/17/2015 ∙ by Xi Zhang, et al. ∙ 0 ∙ share

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Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder

We propose a method for using synthetic data to help learning classifier...
03/11/2015 ∙ by Xi Zhang, et al. ∙ 0 ∙ share

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Hierarchical Maximum-Margin Clustering

We present a hierarchical maximum-margin clustering method for unsupervi...
02/06/2015 ∙ by Guang-Tong Zhou, et al. ∙ 0 ∙ share

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A Unified Semantic Embedding: Relating Taxonomies and Attributes

We propose a method that learns a discriminative yet semantic space for ...
11/18/2014 ∙ by Sung Ju Hwang, et al. ∙ 0 ∙ share

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Dependence Maximizing Temporal Alignment via Squared-Loss Mutual Information

The goal of temporal alignment is to establish time correspondence betwe...
06/19/2012 ∙ by Makoto Yamada, et al. ∙ 0 ∙ share

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High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso

The goal of supervised feature selection is to find a subset of input fe...
02/02/2012 ∙ by Makoto Yamada, et al. ∙ 0 ∙ share

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