1 citations · 4 across the 10 of their papers we have counts for
10 papers
MatIR: A Hybrid Mamba-Transformer Image Restoration Model
Juan Wen, Weiyan Hou, Luc Van Gool +1
In recent years, Transformers-based models have made significant progress in the field of image restoration by leveraging their inherent ability to capture complex contextual featu…
EvenNICER-SLAM: Event-based Neural Implicit Encoding SLAM
Shi Chen, Danda Pani Paudel, Luc Van Gool
The advancement of dense visual simultaneous localization and mapping (SLAM) has been greatly facilitated by the emergence of neural implicit representations. Neural implicit encod…
Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking
Mattia Segu, Luigi Piccinelli, Siyuan Li +3
Multiple object tracking in complex scenarios - such as coordinated dance performances, team sports, or dynamic animal groups - presents unique challenges. In these settings, objec…
Walker: Self-supervised Multiple Object Tracking by Walking on Temporal Appearance Graphs
Mattia Segu, Luigi Piccinelli, Siyuan Li +3
The supervision of state-of-the-art multiple object tracking (MOT) methods requires enormous annotation efforts to provide bounding boxes for all frames of all videos, and instance…
Self-supervised Shape Completion via Involution and Implicit Correspondences
Mengya Liu, Ajad Chhatkuli, Janis Postels +2
3D shape completion is traditionally solved using supervised training or by distribution learning on complete shape examples. Recently self-supervised learning approaches that do n…
SLAck: Semantic, Location, and Appearance Aware Open-Vocabulary Tracking
Siyuan Li, Lei Ke, Yung-Hsu Yang +4
Open-vocabulary Multiple Object Tracking (MOT) aims to generalize trackers to novel categories not in the training set. Currently, the best-performing methods are mainly based on p…