16 citations · 32 across the 6 of their papers we have counts for
6 papers · 1 filter
What Happens Next? Anticipating Future Motion by Generating Point Trajectories
Gabrijel Boduljak, Laurynas Karazija, Iro Laina +2
We consider the problem of forecasting motion from a single image, i.e., predicting how objects in the world are likely to move, without the ability to observe other parameters suc…
Learning segmentation from point trajectories
Laurynas Karazija, Iro Laina, Christian Rupprecht +1
We consider the problem of segmenting objects in videos based on their motion and no other forms of supervision. Prior work has often approached this problem by using the principle…
Diffusion Models for Open-Vocabulary Segmentation
Laurynas Karazija, Iro Laina, Andrea Vedaldi +1
Open-vocabulary segmentation is the task of segmenting anything that can be named in an image. Recently, large-scale vision-language modelling has led to significant advances in op…
Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns
Laurynas Karazija, Subhabrata Choudhury, Iro Laina +2
We propose a new approach to learn to segment multiple image objects without manual supervision. The method can extract objects form still images, but uses videos for supervision.…
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion
Subhabrata Choudhury, Laurynas Karazija, Iro Laina +2
Motion, measured via optical flow, provides a powerful cue to discover and learn objects in images and videos. However, compared to using appearance, it has some blind spots, such…
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
Laurynas Karazija, Iro Laina, Christian Rupprecht
There has been a recent surge in methods that aim to decompose and segment scenes into multiple objects in an unsupervised manner, i.e., unsupervised multi-object segmentation. Per…