18 citations · 64 across the 43 of their papers we have counts for
14 papers · 1 filter
LSVOS 2025 Challenge Report: Recent Advances in Complex Video Object Segmentation
Chang Liu, Henghui Ding, Kaining Ying +46
This report presents an overview of the 7th Large-scale Video Object Segmentation (LSVOS) Challenge held in conjunction with ICCV 2025. Besides the two traditional tracks of LSVOS…
Sa2VA-i: Improving Sa2VA Results with Consistent Training and Inference
Alexey Nekrasov, Ali Athar, Daan de Geus +2
Sa2VA is a recent model for language-guided dense grounding in images and video that achieves state-of-the-art results on multiple segmentation benchmarks and that has become widel…
Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers
Chung-Shien Brian Wang, Christian Schmidt, Jens Piekenbrinck +1
Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models like VGGT, and MapAnything h…
DONUT: A Decoder-Only Model for Trajectory Prediction
Markus Knoche, Daan de Geus, Bastian Leibe
Predicting the motion of other agents in a scene is highly relevant for autonomous driving, as it allows a self-driving car to anticipate. Inspired by the success of decoder-only m…
How do Foundation Models Compare to Skeleton-Based Approaches for Gesture Recognition in Human-Robot Interaction?
Stephanie Käs, Anton Burenko, Louis Markert +4
Gestures enable non-verbal human-robot communication, especially in noisy environments like agile production. Traditional deep learning-based gesture recognition relies on task-spe…
Systematic Comparison of Projection Methods for Monocular 3D Human Pose Estimation on Fisheye Images
Stephanie Käs, Sven Peter, Henrik Thillmann +5
Fisheye cameras offer robots the ability to capture human movements across a wider field of view (FOV) than standard pinhole cameras, making them particularly useful for applicatio…
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting
Jens Piekenbrinck, Christian Schmidt, Alexander Hermans +3
3D Gaussian Splatting (3DGS) has emerged as a powerful representation for neural scene reconstruction, offering high-quality novel view synthesis while maintaining computational ef…
How Important are Videos for Training Video LLMs?
George Lydakis, Alexander Hermans, Ali Athar +2
Research into Video Large Language Models (LLMs) has progressed rapidly, with numerous models and benchmarks emerging in just a few years. Typically, these models are initialized w…
Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving
Alexey Nekrasov, Malcolm Burdorf, Stewart Worrall +2
To operate safely, autonomous vehicles (AVs) need to detect and handle unexpected objects or anomalies on the road. While significant research exists for anomaly detection and segm…
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…
Your ViT is Secretly an Image Segmentation Model
Tommie Kerssies, Niccolò Cavagnero, Alexander Hermans +5
Vision Transformers (ViTs) have shown remarkable performance and scalability across various computer vision tasks. To apply single-scale ViTs to image segmentation, existing method…
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
Severin Heidrich, Till Beemelmanns, Alexey Nekrasov +2
Autonomous driving has the potential to significantly enhance productivity and provide numerous societal benefits. Ensuring robustness in these safety-critical systems is essential…
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…
Panoptic-CUDAL: Rural Australia Point Cloud Dataset in Rainy Conditions
Tzu-Yun Tseng, Alexey Nekrasov, Malcolm Burdorf +5
Existing autonomous driving datasets are predominantly oriented towards well-structured urban settings and favourable weather conditions, leaving the complexities of rural environm…