most citedA Baseline for the Commands For Autonomous Vehicles Challenge

8 citations · 8 across the 1 of their papers we have counts for

collaborators

8 papers

cs.CV2020

Commands 4 Autonomous Vehicles (C4AV) Workshop Summary

Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic +5

The task of visual grounding requires locating the most relevant region or object in an image, given a natural language query. So far, progress on this task was mostly measured on…

cs.CV2020

SCAN: Learning to Classify Images without Labels

Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis +2

Can we automatically group images into semantically meaningful clusters when ground-truth annotations are absent? The task of unsupervised image classification remains an important…

cs.CL20208 cited

A Baseline for the Commands For Autonomous Vehicles Challenge

Simon Vandenhende, Thierry Deruyttere, Dusan Grujicic

The Commands For Autonomous Vehicles (C4AV) challenge requires participants to solve an object referral task in a real-world setting. More specifically, we consider a scenario wher…

cs.CV2020

Multi-Task Learning for Dense Prediction Tasks: A Survey

Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke +3

With the advent of deep learning, many dense prediction tasks, i.e. tasks that produce pixel-level predictions, have seen significant performance improvements. The typical approach…

cs.CV2020

MTI-Net: Multi-Scale Task Interaction Networks for Multi-Task Learning

Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool

In this paper, we argue about the importance of considering task interactions at multiple scales when distilling task information in a multi-task learning setup. In contrast to com…

cs.AI2019

Talk2Car: Taking Control of Your Self-Driving Car

Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic +2

A long-term goal of artificial intelligence is to have an agent execute commands communicated through natural language. In many cases the commands are grounded in a visual environm…