24 citations · 36 across the 10 of their papers we have counts for
6 papers · 1 filter
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models
Yan Xie, Zequn Zeng, Hao Zhang +5
Concept Bottleneck Models (CBMs) try to make the decision-making process transparent by exploring an intermediate concept space between the input image and the output prediction. E…
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…
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…
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…
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…
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling
Hao Zhang, Bo Chen, Long Tian +2
For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that int…