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20122024
most citedDeepGraph: Graph Structure Predicts Network Growth

15 citations · 62 across the 21 of their papers we have counts for

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Showing cs.CVShow all

8 papers · 1 filter

cs.CV2024

Technique Report of CVPR 2024 PBDL Challenges

Ying Fu, Yu Li, Shaodi You +96

The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…

cs.CV2024

VEglue: Testing Visual Entailment Systems via Object-Aligned Joint Erasing

Zhiyuan Chang, Mingyang Li, Junjie Wang +2

Visual entailment (VE) is a multimodal reasoning task consisting of image-sentence pairs whereby a promise is defined by an image, and a hypothesis is described by a sentence. The…

cs.CV2024

DarkShot: Lighting Dark Images with Low-Compute and High-Quality

Jiazhang Zheng, Lei Li, Qiuping Liao +3

Nighttime photography encounters escalating challenges in extremely low-light conditions, primarily attributable to the ultra-low signal-to-noise ratio. For real-world deployment,…

cs.CV2024

AID-DTI: Accelerating High-fidelity Diffusion Tensor Imaging with Detail-Preserving Model-based Deep Learning

Wenxin Fan, Jian Cheng, Cheng Li +6

Deep learning has shown great potential in accelerating diffusion tensor imaging (DTI). Nevertheless, existing methods tend to suffer from Rician noise and detail loss in reconstru…

cs.CV20242 cited

MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning

Jiarun Liu, Hong-Yu Zhou, Cheng Li +4

Existing contrastive language-image pre-training aims to learn a joint representation by matching abundant image-text pairs. However, the number of image-text pairs in medical data…

cs.CV20233 cited

Few-shot Class-incremental Learning for Cross-domain Disease Classification

Hao Yang, Weijian Huang, Jiarun Liu +2

The ability to incrementally learn new classes from limited samples is crucial to the development of artificial intelligence systems for real clinical application. Although existin…