64 citations · 204 across the 20 of their papers we have counts for
9 papers · 1 filter
Tracking-Assisted Segmentation of Biological Cells
Deepak K. Gupta, Nathan de Bruijn, Andreas Panteli +1
U-Net and its variants have been demonstrated to work sufficiently well in biological cell tracking and segmentation. However, these methods still suffer in the presence of complex…
SafeCritic: Collision-Aware Trajectory Prediction
Tessa van der Heiden, Naveen Shankar Nagaraja, Christian Weiss +1
Navigating complex urban environments safely is a key to realize fully autonomous systems. Predicting future locations of vulnerable road users, such as pedestrians and cyclists, t…
Increasing Expressivity of a Hyperspherical VAE
Tim R. Davidson, Jakub M. Tomczak, Efstratios Gavves
Learning suitable latent representations for observed, high-dimensional data is an important research topic underlying many recent advances in machine learning. While traditionally…
3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation
Yunlu Chen, Thomas Mensink, Efstratios Gavves
A key challenge for RGB-D segmentation is how to effectively incorporate 3D geometric information from the depth channel into 2D appearance features. We propose to model the effect…
I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation
Laurens Samson, Nanne van Noord, Olaf Booij +3
Adversarial training has been recently employed for realizing structured semantic segmentation, in which the aim is to preserve higher-level scene structural consistencies in dense…
Model Decay in Long-Term Tracking
Efstratios Gavves, Ran Tao, Deepak K. Gupta +1
Updating the tracker model with adverse bounding box predictions adds an unavoidable bias term to the learning. This bias term, which we refer to as model decay, offsets the learni…