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Dec 13, 2019
Computer Vision
Machine Learning

SPIN: A High Speed, High Resolution Vision Dataset for Tracking and …

We introduce a new high resolution, high frame rate stereo video dataset, which we call SPIN, for tracking and action recognition in the game of ping…
Dec 13, 2019
Machine Learning
Computation and Language

WaLDORf: Wasteless Language-model Distillation On Reading-comprehensi…

Transformer based Very Large Language Models (VLLMs) like BERT, XLNet and RoBERTa, have recently shown tremendous performance on a large variety of N…
Dec 13, 2019
Computer Vision

Action Modifiers: Learning from Adverbs in Instructional Videos

We present a method to learn a representation for adverbs from instructional videos using weak supervision from the accompanying narrations. Key to o…
Dec 13, 2019
Computer Vision
Image and Video Processing

Seeing Around Street Corners: Non-Line-of-Sight Detection and Trackin…

Conventional sensor systems record information about directly visible objects, whereas occluded scene components are considered lost in the measureme…
Dec 13, 2019
Computer Vision
Machine Learning
Multimedia
Image and Video Processing

Music-oriented Dance Video Synthesis with Pose Perceptual Loss

We present a learning-based approach with pose perceptual loss for automatic music video generation. Our method can produce a realistic dance video t…
Dec 13, 2019
Robotics
Artificial Intelligence
Computer Vision
Human-Computer Interaction

That and There: Judging the Intent of Pointing Actions with Robotic A…

Collaborative robotics requires effective communication between a robot and a human partner. This work proposes a set of interpretive principles for …
Dec 13, 2019
Computation and Language

Document Sub-structure in Neural Machine Translation

Current approaches to machine translation (MT) either translate sentences in isolation, disregarding the context they appear in, or model context on …
Dec 13, 2019
Artificial Intelligence

An Interval-Valued Utility Theory for Decision Making with Dempster…

The main goal of this paper is to describe an axiomatic utility theory for Dempster-Shafer belief function lotteries. The axiomatic framework used is…
Dec 13, 2019
Machine Learning

Active emulation of computer codes with Gaussian processes -- Appli…

Many fields of science and engineering rely on running simulations with complex and computationally expensive models to understand the involved proce…
Dec 13, 2019
Computer Science and Game Theory
Artificial Intelligence
Multiagent Systems

Reducing selfish routing inefficiencies using traffic lights

Traffic congestion games abstract away from the costs of junctions in transport networks, yet, in urban environments, these often impact journey time…
Dec 13, 2019
Computer Vision

Inferring Super-Resolution Depth from a Moving Light-Source Enhanced …

A novel approach towards depth map super-resolution using multi-view uncalibrated photometric stereo is presented. Practically, an LED light source i…
Dec 13, 2019
Computer Vision
Image and Video Processing

Latent-Space Laplacian Pyramids for Adversarial Representation Learni…

Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, …
Dec 13, 2019
Computer Vision

Relative planar motion for vehicle-mounted cameras from a single affi…

Two solvers are proposed for estimating the extrinsic camera parameters from a single affine correspondence assuming general planar motion. In this c…
Dec 13, 2019
Computer Vision

Least-squares Optimal Relative Planar Motion for Vehicle-mounted Came…

A new closed-form solver is proposed minimizing the algebraic error optimally, in the least-squares sense, to estimate the relative planar motion of …
Dec 13, 2019
Artificial Intelligence

The KRR and ML areas of AI have been developed independently to a large extent for several decades. It results that most of the researchers in one area are ignorant of what has been going on in the other area. The intended purpose of this joint work…

From Shallow to Deep Interactions Between Knowledge Representation, …

This paper proposes a tentative and original survey of meeting points between Knowledge Representation and Reasoning (KRR) and Machine Learning (ML),…
Dec 13, 2019
Computer Vision

Multi-level Similarity Learning for Low-Shot Recognition

Low-shot learning indicates the ability to recognize unseen objects based on very limited labeled training samples, which simulates human visual inte…
Dec 13, 2019
Computer Vision

Fast Image Caption Generation with Position Alignment

Recent neural network models for image captioning usually employ an encoder-decoder architecture, where the decoder adopts a recursive sequence decod…
Dec 13, 2019
Computer Vision
Machine Learning
Robotics

Our current work contributes to the research area of deictic gestures, specifically pointing gestures, in HRI scenarios by introducing the GWR as a method to model an inherently continuous space, which renders the usage of specific markers or predef…

Solving Visual Object Ambiguities when Pointing: An Unsupervised Le…

Whenever we are addressing a specific object or refer to a certain spatial location, we are using referential or deictic gestures usually accompanied…
Dec 13, 2019
Computer Vision

We introduced a partially supervised setting for generic object counting in natural scenes, and proposed two novel frameworks to enable object counting under this challenging setting. Our frameworks were built on a novel dual-branch architecture hav…

Towards Partial Supervision for Generic Object Counting in Natural …

Generic object counting in natural scenes is a challenging computer vision problem. Existing approaches either rely on instance-level supervision or …
Dec 13, 2019
Computer Vision

In this paper, we have introduced the Forking Paths dataset, and the Multiverse model for multi-future forecasting. Our study is the first to provide a quantitative benchmark and evaluation methodology for multi-future trajectory prediction by using…

The Garden of Forking Paths: Towards Multi-Future Trajectory Predicti…

This paper studies the problem of predicting the distribution over multiple possible future paths of people as they move through various visual scene…
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