1 code implementation • 19 Dec 2023 • Wei Tang, Liang Li, Xuejing Liu, Lu Jin, Jinhui Tang, Zechao Li
In this paper, we propose a novel framework with context disentangling and prototype inheriting for robust visual grounding to handle both scenes.
no code implementations • ICCV 2023 • Xue Wang, Zhibo Wang, Haiqin Weng, Hengchang Guo, Zhifei Zhang, Lu Jin, Tao Wei, Kui Ren
Considering the insufficient study on such complex causal questions, we make the first attempt to explain different causal questions by contrastive explanations in a unified framework, ie., Counterfactual Contrastive Explanation (CCE), which visually and intuitively explains the aforementioned questions via a novel positive-negative saliency-based explanation scheme.
no code implementations • IEEE Transactions on Image Processing 2021 • Xinguang Xiang, YaJie Zhang, Lu Jin, Zechao Li, Jinhui Tang
Specifically, to localize diverse local regions, a sub-region localization module is developed to learn discriminative local features by locating the peaks of non-overlap sub-regions in the feature map.
no code implementations • 9 Jan 2019 • Lu Jin, Zechao Li, Jinhui Tang
In this article, we propose a novel deep semantic multimodal hashing network (DSMHN) for scalable image-text and video-text retrieval.
no code implementations • 7 May 2018 • Lu Jin, Xiangbo Shu, Kai Li, Zechao Li, Guo-Jun Qi, Jinhui Tang
However, most existing deep hashing methods directly learn the hash functions by encoding the global semantic information, while ignoring the local spatial information of images.