36 citations · 112 across the 14 of their papers we have counts for
6 papers · 1 filter
TopoMaskV3: 3D Mask Head with Dense Offset and Height Predictions for Road Topology Understanding
Muhammet Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Mask-based paradigms for road topology understanding, such as TopoMaskV2, offer a complementary alternative to query-based methods by generating centerlines via a dense rasterized…
RQR3D: Reparametrizing the regression targets for BEV-based 3D object detection
Ozsel Kilinc, Cem Tarhan
Accurate, fast, and reliable 3D perception is essential for autonomous driving. Recently, bird's-eye view (BEV)-based perception approaches have emerged as superior alternatives to…
GLane3D : Detecting Lanes with Graph of 3D Keypoints
Halil İbrahim Öztürk, Muhammet Esat Kalfaoğlu, Ozsel Kilinc
Accurate and efficient lane detection in 3D space is essential for autonomous driving systems, where robust generalization is the foremost requirement for 3D lane detection algorit…
TopoBDA: Towards Bezier Deformable Attention for Road Topology Understanding
Muhammet Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Understanding road topology is crucial for autonomous driving. This paper introduces TopoBDA (Topology with Bezier Deformable Attention), a novel approach that enhances road topolo…
TopoMaskV2: Enhanced Instance-Mask-Based Formulation for the Road Topology Problem
M. Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Recently, the centerline has become a popular representation of lanes due to its advantages in solving the road topology problem. To enhance centerline prediction, we have develope…
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture
M. Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Driving scene understanding task involves detecting static elements such as lanes, traffic signs, and traffic lights, and their relationships with each other. To facilitate the dev…