159 citations · 183 across the 10 of their papers we have counts for
10 papers
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…
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…
TarViS: A Unified Approach for Target-based Video Segmentation
Ali Athar, Alexander Hermans, Jonathon Luiten +2
The general domain of video segmentation is currently fragmented into different tasks spanning multiple benchmarks. Despite rapid progress in the state-of-the-art, current methods…
BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video
Ali Athar, Jonathon Luiten, Paul Voigtlaender +4
Multiple existing benchmarks involve tracking and segmenting objects in video e.g., Video Object Segmentation (VOS) and Multi-Object Tracking and Segmentation (MOTS), but there is…
Differentiable Soft-Masked Attention
Ali Athar, Jonathon Luiten, Alexander Hermans +2
Transformers have become prevalent in computer vision due to their performance and flexibility in modelling complex operations. Of particular significance is the 'cross-attention'…
HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images
Ali Athar, Jonathon Luiten, Alexander Hermans +2
Existing state-of-the-art methods for Video Object Segmentation (VOS) learn low-level pixel-to-pixel correspondences between frames to propagate object masks across video. This req…
D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
Christian Schmidt, Ali Athar, Sabarinath Mahadevan +1
Despite receiving significant attention from the research community, the task of segmenting and tracking objects in monocular videos still has much room for improvement. Existing w…
Making a Case for 3D Convolutions for Object Segmentation in Videos
Sabarinath Mahadevan, Ali Athar, Aljoša Ošep +3
The task of object segmentation in videos is usually accomplished by processing appearance and motion information separately using standard 2D convolutional networks, followed by a…
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
Ali Athar, Sabarinath Mahadevan, Aljoša Ošep +2
Existing methods for instance segmentation in videos typically involve multi-stage pipelines that follow the tracking-by-detection paradigm and model a video clip as a sequence of…