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20232026
most citedUniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

38 citations · 70 across the 73 of their papers we have counts for

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39 papers · 1 filter

cs.CV2025

Exo2EgoSyn: Unlocking Foundation Video Generation Models for Exocentric-to-Egocentric Video Synthesis

Mohammad Mahdi, Yuqian Fu, Nedko Savov +3

Foundation video generation models such as WAN 2.2 exhibit strong text- and image-conditioned synthesis abilities but remain constrained to the same-view generation setting. In thi…

cs.CV2025

Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarks

Xu Zheng, Zihao Dongfang, Lutao Jiang +17

Humans possess spatial reasoning abilities that enable them to understand spaces through multimodal observations, such as vision and sound. Large multimodal reasoning models extend…

cs.CV2025

V-SAM: Marrying SAM2 with Multi-Prompt Experts for Cross-View Object Correspondence

Jiancheng Pan, Runze Wang, Tianwen Qian +7

Cross-view object correspondence, exemplified by the representative task of ego-exo object correspondence, aims to establish consistent associations of the same object across diffe…

eess.IV2025

Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priors

Xiaolong Qian, Qi Jiang, Yao Gao +8

Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by training a universal neural network, demons…

cs.CV20251 cited

RefAtomNet++: Advancing Referring Atomic Video Action Recognition using Semantic Retrieval based Multi-Trajectory Mamba

Kunyu Peng, Di Wen, Jia Fu +9

Referring Atomic Video Action Recognition (RAVAR) aims to recognize fine-grained, atomic-level actions of a specific person of interest conditioned on natural language descriptions…

cs.CV2025

MOBIUS: Big-to-Mobile Universal Instance Segmentation via Multi-modal Bottleneck Fusion and Calibrated Decoder Pruning

Mattia Segu, Marta Tintore Gazulla, Yongqin Xian +2

Scaling up model size and training data has advanced foundation models for instance-level perception, achieving state-of-the-art in-domain and zero-shot performance across object d…