9 papers
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…
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…
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…
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…
OoDIS: Anomaly Instance Segmentation and Detection Benchmark
Alexey Nekrasov, Rui Zhou, Miriam Ackermann +3
Safe navigation of self-driving cars and robots requires a precise understanding of their environment. Training data for perception systems cannot cover the wide variety of objects…