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Mar 20, 2018
Conferences: CVPR
Computer Vision

Actor and Action Video Segmentation from a Sentence

This paper strives for pixel-level segmentation of actors and their actions in video content. Different from existing works, which all learn to segme…
Apr 20, 2019
Signal Processing
Computer Vision
Human-Computer Interaction

Temporal Unet: Sample Level Human Action Recognition using WiFi

Human doing actions will result in WiFi distortion, which is widely explored for action recognition, such as the elderly fallen detection, hand sign …
Feb 19, 2017
Computer Vision

Zoom Out-and-In Network with Recursive Training for Object Proposal

In this paper, we propose a zoom-out-and-in network for generating object proposals. We utilize different resolutions of feature maps in the network …
Jul 06, 2018
Computer Vision

Dynamic Multimodal Instance Segmentation guided by natural language …

In this paper, we address the task of segmenting an object given a natural language expression that references it, \textit{i.e.} a referring expressi…
Jan 25, 2018
Conferences: CVPR
Computer Vision
Artificial Intelligence
Computation and Language

MAttNet: Modular Attention Network for Referring Expression Compreh…

In this paper, we address referring expression comprehension: localizing an image region described by a natural language expression. While most recen…
Sep 03, 2019
Computer Vision
Artificial Intelligence
Computation and Language

Data Interpretation over Plots

Reasoning over plots by question answering (QA) is a challenging machine learning task at the intersection of vision, language processing, and reason…
Sep 21, 2019
Computer Vision

In this paper, we proposed a BB generator and a positive RoI generator. We showed that generated RoIs can be used both as an analysis tool (owing to its controllable nature) and a training method for the two-stage object detectors.

Generating Positive Bounding Boxes for Balanced Training of Object …

Two-stage deep object detectors generate a set of regions-of-interest (RoI) in the first stage, then, in the second stage, identify objects among the…
Dec 12, 2019
Computer Vision
Computation and Language
Machine Learning

In this work, we have shown the benefits of using fine-tuning from a close domain in the context of table detection. In addition to the accuracy improvement, this approach avoids overfitting and solves the problem of having a small dataset. Moreover…

The Benefits of Close-Domain Fine-Tuning for Table Detection in Docum…

A correct localisation of tables in a document is instrumental for determining their structure and extracting their contents; therefore, table detect…
Dec 04, 2016
Computer Vision

Learning to Segment Object Proposals via Recursive Neural Networks

To avoid the exhaustive search over locations and scales, current state-of-the-art object detection systems usually involve a crucial component gener…
Sep 30, 2018
Computer Vision
Machine Learning

CaTDet: Cascaded Tracked Detector for Efficient Object Detection from…

Detecting objects in a video is a compute-intensive task. In this paper we propose CaTDet, a system to speedup object detection by leveraging the tem…
Sep 21, 2019
Computer Vision

Generating Positive Bounding Boxes for Balanced Training of Object …

Two-stage deep object detectors generate a set of regions-of-interest (RoI) in the first stage, then, in the second stage, identify objects among the…
Apr 09, 2019
Computer Vision
Computation and Language

Cross-Modal Self-Attention Network for Referring Image Segmentation

We consider the problem of referring image segmentation. Given an input image and a natural language expression, the goal is to segment the object re…
Nov 21, 2008

Production of fragments with and without strangeness within a combine…

The formation of hypernuclei in hadron-induced reactions and in heavy-ion collisions within a combination of a covariant transport model and a statis…
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