8 citations · 16 across the 7 of their papers we have counts for
8 papers
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…
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image Classification
Zequn Zeng, Yudi Su, Jianqiao Sun +6
Concept-based models can map black-box representations to human-understandable concepts, which makes the decision-making process more transparent and then allows users to understan…
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…
Memory-Efficient Network for Large-scale Video Compressive Sensing
Ziheng Cheng, Bo Chen, Guanliang Liu +4
Video snapshot compressive imaging (SCI) captures a sequence of video frames in a single shot using a 2D detector. The underlying principle is that during one exposure time, differ…