17 citations · 28 across the 11 of their papers we have counts for
11 papers
Lidar Panoptic Segmentation in an Open World
Anirudh S Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu +4
Addressing Lidar Panoptic Segmentation (LPS ) is crucial for safe deployment of autonomous vehicles. LPS aims to recognize and segment lidar points w.r.t. a pre-defined vocabulary…
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation
Linyan Yang, Lukas Hoyer, Mark Weber +6
Unsupervised Domain Adaptation (UDA) is the task of bridging the domain gap between a labeled source domain, e.g., synthetic data, and an unlabeled target domain. We observe that c…
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation
Aysim Toker, Marvin Eisenberger, Daniel Cremers +1
In recent years, semantic segmentation has become a pivotal tool in processing and interpreting satellite imagery. Yet, a prevalent limitation of supervised learning techniques rem…
SeMoLi: What Moves Together Belongs Together
Jenny Seidenschwarz, Aljoša Ošep, Francesco Ferroni +2
We tackle semi-supervised object detection based on motion cues. Recent results suggest that heuristic-based clustering methods in conjunction with object trackers can be used to p…
Lidar Panoptic Segmentation and Tracking without Bells and Whistles
Abhinav Agarwalla, Xuhua Huang, Jason Ziglar +5
State-of-the-art lidar panoptic segmentation (LPS) methods follow bottom-up segmentation-centric fashion wherein they build upon semantic segmentation networks by utilizing cluster…
NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation
Tim Meinhardt, Matt Feiszli, Yuchen Fan +2
Until recently, the Video Instance Segmentation (VIS) community operated under the common belief that offline methods are generally superior to a frame by frame online processing.…