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20182026
most citedExploring the Benefits of Vision Foundation Models for Unsupervised Domain Adaptation

1 citations · 2 across the 14 of their papers we have counts for

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cs.CV2026

A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens

Tommie Kerssies, Gabriele Berton, Ju He +5

Anticipating diverse future states is a central challenge in video world modeling. Discriminative world models produce a deterministic prediction that implicitly averages over poss…

cs.CV2026

PMT: Plain Mask Transformer for Image and Video Segmentation with Frozen Vision Encoders

Niccolò Cavagnero, Narges Norouzi, Gijs Dubbelman +1

Vision Foundation Models (VFMs) pre-trained at scale enable a single frozen encoder to serve multiple downstream tasks simultaneously. Recent VFM-based encoder-only models for imag…

cs.CV2026

VidEoMT: Your ViT is Secretly Also a Video Segmentation Model

Narges Norouzi, Idil Esen Zulfikar, Niccolò Cavagnero +4

Existing online video segmentation models typically combine a per-frame segmenter with complex specialized tracking modules. While effective, these modules introduce significant ar…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…