1 code implementation • 12 Mar 2024 • Jiawei Zhang, Jiahe Li, Lei Huang, Xiaohan Yu, Lin Gu, Jin Zheng, Xiao Bai
With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains.
no code implementations • 8 Mar 2024 • Tianyu Xiong, Xiaohan Yu
In the era of information overload, the value of recommender systems has been profoundly recognized in academia and industry alike.
no code implementations • 7 Feb 2024 • Xiaohan Yu, Li Zhang, Xin Zhao, Yue Wang, Zhongrui Ma
To address this limitation, we propose a new paradigm, ID representation, which incorporates pre-trained ID embeddings into LLMs in a complementary manner.
1 code implementation • 1 Nov 2023 • Anuroop Sriram, Sihoon Choi, Xiaohan Yu, Logan M. Brabson, Abhishek Das, Zachary Ulissi, Matt Uyttendaele, Andrew J. Medford, David S. Sholl
We also trained state-of-the-art ML models on this dataset to approximate calculations at the DFT level.
no code implementations • 29 Jan 2022 • Xiaohan Yu, Shaochen Mao
Attentive Neural Process (ANP) improves the fitting ability of Neural Process (NP) and improves its prediction accuracy, but the higher time complexity of the model imposes a limitation on the length of the input sequence.
no code implementations • 25 Sep 2021 • Yajie Sun, Miaohua Zhang, Xiaohan Yu, Yi Liao, Yongsheng Gao
Motivated by these issues, this paper proposes a novel compositional feature embedding and similarity metric (CECS).
no code implementations • 16 Sep 2021 • Zicheng Pan, Xiaohan Yu, Miaohua Zhang, Yongsheng Gao
The advantage of the proposed method is that the feature detection and extraction model only requires a small amount of target region samples with bounding boxes for training, then it can automatically locate the target area for a large number of images in the dataset at a high detection accuracy.
no code implementations • 25 Aug 2021 • Jun Wang, Hefeng Zhou, Xiaohan Yu
There are two main problems hindering the performance of the two-phase WSOD approaches, i. e., insufficient learning problem and strict reliance between the FSD and the pseudo ground truth (PGT) generated by the WSOD model.
1 code implementation • 6 Jul 2021 • Jun Wang, Xiaohan Yu, Yongsheng Gao
We verify the effectiveness of FFVT on three benchmarks where FFVT achieves the state-of-the-art performance.
Ranked #6 on Fine-Grained Image Classification on CUB-200-2011
Fine-Grained Image Classification Fine-Grained Visual Categorization
1 code implementation • 3 Jul 2021 • Jun Wang, Yang Zhao, Linglong Qian, Xiaohan Yu, Yongsheng Gao
The precise detection of blood vessels in retinal images is crucial to the early diagnosis of the retinal vascular diseases, e. g., diabetic, hypertensive and solar retinopathies.
2 code implementations • 4 Feb 2021 • Jun Wang, Xiaohan Yu, Yongsheng Gao
Specifically, the proposed MGA integrates a pre-trained semantic segmentation model that produces auxiliary supervision signal, i. e., patchy attention mask, enabling a discriminative representation learning.
1 code implementation • ICCV 2021 • Xiaohan Yu, Yang Zhao, Yongsheng Gao, Xiaohui Yuan, Shengwu Xiong
The proposed UFG image dataset and evaluation protocols is intended to serve as a benchmark platform that can advance research of visual classification from approaching human performance to beyond human ability, via facilitating benchmark data of artificial intelligence (AI) not to be limited by the labels of human intelligence (HI).
no code implementations • Findings of the Association for Computational Linguistics 2020 • Xiaohan Yu, Quzhe Huang, Zheng Wang, Yansong Feng, Dongyan Zhao
Code comments are vital for software maintenance and comprehension, but many software projects suffer from the lack of meaningful and up-to-date comments in practice.
1 code implementation • 2 Dec 2019 • Xiaohan Yu, Yang Zhao, Yongsheng Gao, Shengwu Xiong, Xiaohui Yuan
To address above limitations, this paper proposes a novel Multi-Orientation Region Transform (MORT), which can effectively characterize both contour and structure features simultaneously, for patchy image structure classification.
no code implementations • 11 Oct 2019 • Bin Wang, Yongsheng Gao, Xiaohan Yu, Xiaohui Yuan, Shengwu Xiong, Xianzhong Feng
Encouraging experimental results of the proposed method in comparison to the state-of-the-art leaf species recognition methods demonstrate the availability of cultivar information in soybean leaves and effectiveness of the proposed MSCM for soybean cultivar identification, which may advance the research in leaf recognition from species to cultivar.
1 code implementation • 25 Feb 2019 • Yuxuan Lai, Yansong Feng, Xiaohan Yu, Zheng Wang, Kun Xu, Dongyan Zhao
Short text matching often faces the challenges that there are great word mismatch and expression diversity between the two texts, which would be further aggravated in languages like Chinese where there is no natural space to segment words explicitly.