most citedHICEScore: A Hierarchical Metric for Image Captioning Evaluation

3 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20243 cited

HICEScore: A Hierarchical Metric for Image Captioning Evaluation

Zequn Zeng, Jianqiao Sun, Hao Zhang +5

Image captioning evaluation metrics can be divided into two categories, reference-based metrics and reference-free metrics. However, reference-based approaches may struggle to eval…

cs.CV20242 cited

MeaCap: Memory-Augmented Zero-shot Image Captioning

Zequn Zeng, Yan Xie, Hao Zhang +3

Zero-shot image captioning (IC) without well-paired image-text data can be divided into two categories, training-free and text-only-training. Generally, these two types of methods…

cs.CV2024

SnapCap: Efficient Snapshot Compressive Video Captioning

Jianqiao Sun, Yudi Su, Hao Zhang +5

Video Captioning (VC) is a challenging multi-modal task since it requires describing the scene in language by understanding various and complex videos. For machines, the traditiona…

cs.CV20231 cited

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification

Miaoge Li, Dongsheng Wang, Xinyang Liu +4

Multi-label image classification is a prediction task that aims to identify more than one label from a given image. This paper considers the semantic consistency of the latent spac…

cs.CV20232 cited

ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based Polishing

Zequn Zeng, Hao Zhang, Zhengjue Wang +3

Zero-shot capability has been considered as a new revolution of deep learning, letting machines work on tasks without curated training data. As a good start and the only existing o…