3 citations · 3 across the 1 of their papers we have counts for
5 papers
Efficient Full Image Interactive Segmentation by Leveraging Within-image Appearance Similarity
Mykhaylo Andriluka, Stefano Pellegrini, Stefan Popov +1
We propose a new approach to interactive full-image semantic segmentation which enables quickly collecting training data for new datasets with previously unseen semantic classes (A…
CoReNet: Coherent 3D scene reconstruction from a single RGB image
Stefan Popov, Pablo Bauszat, Vittorio Ferrari
Advances in deep learning techniques have allowed recent work to reconstruct the shape of a single object given only one RBG image as input. Building on common encoder-decoder arch…
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds
Albert Pumarola, Stefan Popov, Francesc Moreno-Noguer +1
Flow-based generative models have highly desirable properties like exact log-likelihood evaluation and exact latent-variable inference, however they are still in their infancy and…
Large-scale interactive object segmentation with human annotators
Rodrigo Benenson, Stefan Popov, Vittorio Ferrari
Manually annotating object segmentation masks is very time consuming. Interactive object segmentation methods offer a more efficient alternative where a human annotator and a machi…
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova, Hassan Rom, Neil Alldrin +9
We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creativ…