1.4k citations · 1.9k across the 39 of their papers we have counts for
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Masked Vision-Language Transformer in Fashion
Ge-Peng Ji, Mingcheng Zhuge, Dehong Gao +3
We present a masked vision-language transformer (MVLT) for fashion-specific multi-modal representation. Technically, we simply utilize vision transformer architecture for replacing…
TT-NF: Tensor Train Neural Fields
Anton Obukhov, Mikhail Usvyatsov, Christos Sakaridis +2
Learning neural fields has been an active topic in deep learning research, focusing, among other issues, on finding more compact and easy-to-fit representations. In this paper, we…
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
David Bruggemann, Christos Sakaridis, Prune Truong +1
Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UD…
L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras
Kevin Ta, David Bruggemann, Tim Brödermann +2
As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research. In particular, event cameras have emerged…
HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection
Tim Broedermann, Christos Sakaridis, Dengxin Dai +1
Besides standard cameras, autonomous vehicles typically include multiple additional sensors, such as lidars and radars, which help acquire richer information for perceiving the con…
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior
Vaishakh Patil, Christos Sakaridis, Alexander Liniger +1
Monocular depth estimation is vital for scene understanding and downstream tasks. We focus on the supervised setup, in which ground-truth depth is available only at training time.…
LiDAR Snowfall Simulation for Robust 3D Object Detection
Martin Hahner, Christos Sakaridis, Mario Bijelic +4
3D object detection is a central task for applications such as autonomous driving, in which the system needs to localize and classify surrounding traffic agents, even in the presen…