b'Stephen Gould'

research

∙ 03/05/2022

Bridging the Gap Between Learning in Discrete and Continuous Environments for Vision-and-Language Navigation

Most existing works in vision-and-language navigation (VLN) focus on eit...

Yicong Hong, et al. ∙

research

∙ 02/24/2022

Exploiting Problem Structure in Deep Declarative Networks: Two Case Studies

Deep declarative networks and other recent related works have shown how ...

Stephen Gould, et al. ∙

research

∙ 12/03/2021

Efficient Two-Stage Detection of Human-Object Interactions with a Novel Unary-Pairwise Transformer

Recent developments in transformer models for visual data have led to si...

Frederic Z. Zhang, et al. ∙

research

∙ 10/06/2021

A Regularized Wasserstein Framework for Graph Kernels

We propose a learning framework for graph kernels, which is theoreticall...

Asiri Wijesinghe, et al. ∙

research

∙ 08/09/2021

Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models

We extend the task of composed image retrieval, where an input query con...

Zheyuan Liu, et al. ∙

research

∙ 06/21/2021

DiGS : Divergence guided shape implicit neural representation for unoriented point clouds

Neural shape representations have recently shown to be effective in shap...

Yizhak Ben-Shabat, et al. ∙

research

∙ 06/10/2021

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?

Understanding classifier decision under novel environments is central to...

Weijian Deng, et al. ∙

research

∙ 01/02/2021

Semantics for Robotic Mapping, Perception and Interaction: A Survey

For robots to navigate and interact more richly with the world around th...

Sourav Garg, et al. ∙

research

∙ 12/12/2020

Fine-grained Classification via Categorical Memory Networks

Motivated by the desire to exploit patterns shared across classes, we pr...

Weijian Deng, et al. ∙

research

∙ 12/11/2020

Spatio-attentive Graphs for Human-Object Interaction Detection

We address the problem of detecting human–object interactions in images ...

Frederic Z. Zhang, et al. ∙

research

∙ 12/03/2020

Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking

Despite the recent advances in multiple object tracking (MOT), achieved ...

Fatemeh Saleh, et al. ∙

research

∙ 11/26/2020

A Recurrent Vision-and-Language BERT for Navigation

Accuracy of many visiolinguistic tasks has benefited significantly from ...

Yicong Hong, et al. ∙

research

∙ 11/25/2020

How to train your conditional GAN: An approach using geometrically structured latent manifolds

Conditional generative modeling typically requires capturing one-to-many...

Sameera Ramasinghe, et al. ∙

research

∙ 10/19/2020

Language and Visual Entity Relationship Graph for Agent Navigation

Vision-and-Language Navigation (VLN) requires an agent to navigate in a ...

Yicong Hong, et al. ∙

research

∙ 10/13/2020

DORi: Discovering Object Relationship for Moment Localization of a Natural-Language Query in Video

This paper studies the task of temporal moment localization in a long un...

Cristian Rodriguez Opazo, et al. ∙

research

∙ 10/07/2020

Conditional Generative Modeling via Learning the Latent Space

Although deep learning has achieved appealing results on several machine...

Sameera Ramasinghe, et al. ∙

research

∙ 07/29/2020

Solving the Blind Perspective-n-Point Problem End-To-End With Robust Differentiable Geometric Optimization

Blind Perspective-n-Point (PnP) is the problem of estimating the positio...

Dylan Campbell, et al. ∙

research

∙ 07/01/2020

The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose

The availability of a large labeled dataset is a key requirement for app...

Yizhak Ben-Shabat, et al. ∙

research

∙ 06/22/2020

Bidirectional Self-Normalizing Neural Networks

The problem of exploding and vanishing gradients has been a long-standin...

Yao Lu, et al. ∙

research

∙ 05/27/2020

A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews

Despite the recent advances in opinion mining for written reviews, few w...

Edison Marrese-Taylor, et al. ∙

research

∙ 04/28/2020

Inferring Temporal Compositions of Actions Using Probabilistic Automata

This paper presents a framework to recognize temporal compositions of at...

Rodrigo Santa Cruz, et al. ∙

research

∙ 04/16/2020

ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking

One of the core components in online multiple object tracking (MOT) fram...

Fatemeh Saleh, et al. ∙

research

∙ 04/06/2020

Sub-Instruction Aware Vision-and-Language Navigation

Vision-and-language navigation requires an agent to navigate through a r...

Yicong Hong, et al. ∙

research

∙ 03/23/2020

DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares

We propose a surface fitting method for unstructured 3D point clouds. Th...

Yizhak Ben-Shabat, et al. ∙

research

∙ 03/17/2020

Learning to Structure an Image with Few Colors

Color and structure are the two pillars that construct an image. Usually...

Yunzhong Hou, et al. ∙

research

∙ 02/26/2020

Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization

We address the problem of joint optical flow and camera motion estimatio...

Shihao Jiang, et al. ∙

research

∙ 12/18/2019

Sampling Good Latent Variables via CPP-VAEs: VAEs with Condition Posterior as Prior

In practice, conditional variational autoencoders (CVAEs) perform condit...

Sadegh Aliakbarian, et al. ∙

research

∙ 12/04/2019

Spectral-GANs for High-Resolution 3D Point-cloud Generation

Point-clouds are a popular choice for vision and graphics tasks due to t...

Sameera Ramasinghe, et al. ∙

research

∙ 11/30/2019

Representation Learning on Unit Ball with 3D Roto-Translational Equivariance

Convolution is an integral operation that defines how the shape of one f...

Sameera Ramasinghe, et al. ∙

research

∙ 09/11/2019

Deep Declarative Networks: A New Hope

We introduce a new class of end-to-end learnable models wherein data pro...

Stephen Gould, et al. ∙

research

∙ 08/24/2019

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes

Existing networks directly learn feature representations on 3D point clo...

Sameera Ramasinghe, et al. ∙

research

∙ 08/20/2019

Proposal-free Temporal Moment Localization of a Natural-Language Query in Video using Guided Attention

This paper studies the problem of temporal moment localization in a long...

Cristian Rodriguez Opazo, et al. ∙

research

∙ 08/02/2019

Learning Variations in Human Motion via Mix-and-Match Perturbation

Human motion prediction is a stochastic process: Given an observed seque...

Mohammad Sadegh Aliakbarian, et al. ∙

research

∙ 06/14/2019

A Signal Propagation Perspective for Pruning Neural Networks at Initialization

Network pruning is a promising avenue for compressing deep neural networ...

Namhoon Lee, et al. ∙

research

∙ 04/29/2019

Learning to Find Common Objects Across Image Collections

We address the problem of finding a set of images containing a common, b...

Amirreza Shaban, et al. ∙

research

∙ 12/04/2018

The Alignment of the Spheres: Globally-Optimal Spherical Mixture Alignment for Camera Pose Estimation

Determining the position and orientation of a calibrated camera from a s...

Dylan Campbell, et al. ∙

research

∙ 06/15/2018

Partially-Supervised Image Captioning

Image captioning models are becoming increasingly successful at describi...

Peter Anderson, et al. ∙

research

∙ 03/27/2018

Non-Linear Temporal Subspace Representations for Activity Recognition

Representations that can compactly and effectively capture the temporal ...

Anoop Cherian, et al. ∙

research

∙ 03/26/2018

Video Representation Learning Using Discriminative Pooling

Popular deep models for action recognition in videos generate independen...

Jue Wang, et al. ∙

research

∙ 01/26/2018

Neural Algebra of Classifiers

The world is fundamentally compositional, so it is natural to think of v...

Rodrigo Santa Cruz, et al. ∙

research

∙ 11/20/2017

Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

A robot that can carry out a natural-language instruction has been a dre...

Peter Anderson, et al. ∙

research

∙ 09/19/2017

Human Action Forecasting by Learning Task Grammars

For effective human-robot interaction, it is important that a robotic as...

Tengda Han, et al. ∙

research

∙ 07/25/2017

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

Top-down visual attention mechanisms have been used extensively in image...

Peter Anderson, et al. ∙

research

∙ 07/24/2017

Human Pose Forecasting via Deep Markov Models

Human pose forecasting is an important problem in computer vision with a...

Sam Toyer, et al. ∙

research

∙ 06/06/2017

Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation

Pixel-level annotations are expensive and time consuming to obtain. Henc...

Fatemeh Sadat Saleh, et al. ∙

research

∙ 05/30/2017

Discriminatively Learned Hierarchical Rank Pooling Networks

In this work, we present novel temporal encoding methods for action and ...

Basura Fernando, et al. ∙

research

∙ 04/10/2017

DeepPermNet: Visual Permutation Learning

We present a principled approach to uncover the structure of visual data...

Rodrigo Santa Cruz, et al. ∙

research

∙ 04/07/2017

Generalized Rank Pooling for Activity Recognition

Most popular deep models for action recognition split video sequences in...

Anoop Cherian, et al. ∙

research

∙ 04/06/2017

Action Representation Using Classifier Decision Boundaries

Most popular deep learning based models for action recognition are desig...

Jue Wang, et al. ∙

research

∙ 01/19/2017

Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition

Most successful deep learning algorithms for action recognition extend m...

Anoop Cherian, et al. ∙

Stephen Gould

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