activity
20192025
most citedMemory-Efficient Network for Large-scale Video Compressive Sensing

8 citations · 20 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024★ 3 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.CV2024★ 2 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.CV2023★ 2 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…

eess.IV2022★ 2 cited

Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms

Siming Zheng, Yujia Xue, Waleed Tahir +6

We consider the image and video compression on resource limited platforms. An ultra low-cost image encoder, named Block Modulating Video Compression (BMVC) with an encoding complex…

eess.IV2021★ 8 cited

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…

eess.IV2021★ 3 cited

MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing

Zhengjue Wang, Hao Zhang, Ziheng Cheng +2

To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks a…

cs.CV2019

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…