801 citations · 941 across the 11 of their papers we have counts for
15 papers
Self-Supervised Learning with a Multi-Task Latent Space Objective
Pierre-François De Plaen, Abhishek Jha, Luc Van Gool +2
We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment task, solved by a dedicated predic…
Camera-Only 3D Panoptic Scene Completion for Autonomous Driving through Differentiable Object Shapes
Nicola Marinello, Simen Cassiman, Jonas Heylen +2
Autonomous vehicles need a complete map of their surroundings to plan and act. This has sparked research into the tasks of 3D occupancy prediction, 3D scene completion, and 3D pano…
Adversarial Dependence Minimization
Pierre-François De Plaen, Tinne Tuytelaars, Marc Proesmans +1
Minimally redundant representations are typically learned by minimizing feature covariance. However, covariance-based methods fail to eliminate all dependencies/redundancies, as li…
Contrastive Learning for Multi-Object Tracking with Transformers
Pierre-François De Plaen, Nicola Marinello, Marc Proesmans +2
The DEtection TRansformer (DETR) opened new possibilities for object detection by modeling it as a translation task: converting image features into object-level representations. Pr…
Unbalanced Optimal Transport: A Unified Framework for Object Detection
Henri De Plaen, Pierre-François De Plaen, Johan A. K. Suykens +3
During training, supervised object detection tries to correctly match the predicted bounding boxes and associated classification scores to the ground truth. This is essential to de…
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM
Nicola Marinello, Marc Proesmans, Luc Van Gool
3D object tracking is a critical task in autonomous driving systems. It plays an essential role for the system's awareness about the surrounding environment. At the same time there…