1.4k citations · 4.9k across the 44 of their papers we have counts for
6 papers · 1 filter
Learning to Discover and Detect Objects
Vladimir Fomenko, Ismail Elezi, Deva Ramanan +2
We tackle the problem of novel class discovery and localization (NCDL). In this setting, we assume a source dataset with supervision for only some object classes. Instances of othe…
Multi-Object Tracking and Segmentation via Neural Message Passing
Guillem Braso, Orcun Cetintas, Laura Leal-Taixe
Graphs offer a natural way to formulate Multiple Object Tracking (MOT) and Multiple Object Tracking and Segmentation (MOTS) within the tracking-by-detection paradigm. However, they…
Simple Cues Lead to a Strong Multi-Object Tracker
Jenny Seidenschwarz, Guillem Brasó, Victor Castro Serrano +2
For a long time, the most common paradigm in Multi-Object Tracking was tracking-by-detection (TbD), where objects are first detected and then associated over video frames. For asso…
Text2Pos: Text-to-Point-Cloud Cross-Modal Localization
Manuel Kolmet, Qunjie Zhou, Aljosa Osep +1
Natural language-based communication with mobile devices and home appliances is becoming increasingly popular and has the potential to become natural for communicating with mobile…
The Group Loss++: A deeper look into group loss for deep metric learning
Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner +4
Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings…
Is Geometry Enough for Matching in Visual Localization?
Qunjie Zhou, Sérgio Agostinho, Aljosa Osep +1
In this paper, we propose to go beyond the well-established approach to vision-based localization that relies on visual descriptor matching between a query image and a 3D point clo…