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20222024
most citedEfficient Multimodal Learning from Data-centric Perspective

13 citations · 37 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024★ 2 cited

SpatialBot: Precise Spatial Understanding with Vision Language Models

Wenxiao Cai, Iaroslav Ponomarenko, Jianhao Yuan +4

Vision Language Models (VLMs) have achieved impressive performance in 2D image understanding, however they are still struggling with spatial understanding which is the foundation o…

cs.CV2024

FlexiFilm: Long Video Generation with Flexible Conditions

Yichen Ouyang, jianhao Yuan, Hao Zhao +2

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generati…

cs.CV2024★ 1 cited

kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies

Zhongrui Gui, Shuyang Sun, Runjia Li +5

Continual segmentation has not yet tackled the challenge of improving open-vocabulary segmentation models with training data for accurate segmentation across large, continually exp…

cs.CV2024★ 1 cited

SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Model

Bin Cao, Jianhao Yuan, Yexin Liu +4

In the rapidly evolving area of image synthesis, a serious challenge is the presence of complex artifacts that compromise perceptual realism of synthetic images. To alleviate artif…

cs.CV2024★ 13 cited

Efficient Multimodal Learning from Data-centric Perspective

Muyang He, Yexin Liu, Boya Wu +4

Multimodal Large Language Models (MLLMs) have demonstrated notable capabilities in general visual understanding and reasoning tasks. However, their deployment is hindered by substa…

cs.CV2022★ 3 cited

Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators

Jianhao Yuan, Francesco Pinto, Adam Davies +1

Neural image classifiers are known to undergo severe performance degradation when exposed to inputs that are sampled from environmental conditions that differ from their training d…