23 citations · 25 across the 5 of their papers we have counts for
6 papers
Volume Transformer: Revisiting Vanilla Transformers for 3D Scene Understanding
Kadir Yilmaz, Adrian Kruse, Tristan Höfer +2
Transformers have become a common foundation across deep learning, yet 3D scene understanding still relies on specialized backbones with strong domain priors. This isolates the fie…
Acquisition of high-quality images for camera calibration in robotics applications via speech prompts
Timm Linder, Kadir Yilmaz, David B. Adrian +1
Accurate intrinsic and extrinsic camera calibration can be an important prerequisite for robotic applications that rely on vision as input. While there is ongoing research on enabl…
DINO in the Room: Leveraging 2D Foundation Models for 3D Segmentation
Karim Knaebel, Kadir Yilmaz, Daan de Geus +4
Vision foundation models (VFMs) trained on large-scale image datasets provide high-quality features that have significantly advanced 2D visual recognition. However, their potential…
Interactive4D: Interactive 4D LiDAR Segmentation
Ilya Fradlin, Idil Esen Zulfikar, Kadir Yilmaz +2
Interactive segmentation has an important role in facilitating the annotation process of future LiDAR datasets. Existing approaches sequentially segment individual objects at each…
Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook
Reza Azad, Moein Heidary, Kadir Yilmaz +5
Semantic image segmentation, the process of classifying each pixel in an image into a particular class, plays an important role in many visual understanding systems. As the predomi…
Mask4Former: Mask Transformer for 4D Panoptic Segmentation
Kadir Yilmaz, Jonas Schult, Alexey Nekrasov +1
Accurately perceiving and tracking instances over time is essential for the decision-making processes of autonomous agents interacting safely in dynamic environments. With this int…