34 citations · 68 across the 6 of their papers we have counts for
10 papers
A Simple and Generalist Approach for Panoptic Segmentation
Nedyalko Prisadnikov, Wouter Van Gansbeke, Danda Pani Paudel +1
Panoptic segmentation is an important computer vision task, where the current state-of-the-art solutions require specialized components to perform well. We propose a simple general…
Investigating the Effectiveness of Cross-Attention to Unlock Zero-Shot Editing of Text-to-Video Diffusion Models
Saman Motamed, Wouter Van Gansbeke, Luc Van Gool
With recent advances in image and video diffusion models for content creation, a plethora of techniques have been proposed for customizing their generated content. In particular, m…
A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting
Wouter Van Gansbeke, Bert De Brabandere
Panoptic and instance segmentation networks are often trained with specialized object detection modules, complex loss functions, and ad-hoc post-processing steps to manage the perm…
Discovering Object Masks with Transformers for Unsupervised Semantic Segmentation
Wouter Van Gansbeke, Simon Vandenhende, Luc Van Gool
The task of unsupervised semantic segmentation aims to cluster pixels into semantically meaningful groups. Specifically, pixels assigned to the same cluster should share high-level…
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis +1
Contrastive self-supervised learning has outperformed supervised pretraining on many downstream tasks like segmentation and object detection. However, current methods are still pri…
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis +1
Being able to learn dense semantic representations of images without supervision is an important problem in computer vision. However, despite its significance, this problem remains…