1 code implementation • ECCV 2020 • Ziyi Meng, Jiawei Ma, Xin Yuan
Coded aperture snapshot spectral imaging (CASSI) is an effective tool to capture real-world 3D hyperspectral images.
Ranked #9 on
Spectral Reconstruction
on Real HSI
1 code implementation • 3 Dec 2024 • Qisen Wang, Yifan Zhao, Jiawei Ma, Jia Li
However, the diffusion model, as an external prior that can directly provide visual supervision, has always underperformed in sparse-view 3D reconstruction using Score Distillation Sampling (SDS) due to the low information entropy of sparse views compared to text, leading to optimization challenges caused by mode deviation.
no code implementations • 28 May 2024 • Jiawei Ma, Yulei Niu, Shiyuan Huang, Guangxing Han, Shih-Fu Chang
Language has been useful in extending the vision encoder to data from diverse distributions without empirical discovery in training domains.
1 code implementation • CVPR 2024 • Jiawei Ma, Po-Yao Huang, Saining Xie, Shang-Wen Li, Luke Zettlemoyer, Shih-Fu Chang, Wen-tau Yih, Hu Xu
The success of contrastive language-image pretraining (CLIP) relies on the supervision from the pairing between images and captions, which tends to be noisy in web-crawled data.
1 code implementation • CVPR 2023 • Han Lin, Guangxing Han, Jiawei Ma, Shiyuan Huang, Xudong Lin, Shih-Fu Chang
Vision Transformers (ViTs) emerge to achieve impressive performance on many data-abundant computer vision tasks by capturing long-range dependencies among local features.
1 code implementation • CVPR 2023 • Jiawei Ma, Yulei Niu, Jincheng Xu, Shiyuan Huang, Guangxing Han, Shih-Fu Chang
Generalized few-shot object detection aims to achieve precise detection on both base classes with abundant annotations and novel classes with limited training data.
1 code implementation • 28 Dec 2022 • Yuncong Yang, Jiawei Ma, Shiyuan Huang, Long Chen, Xudong Lin, Guangxing Han, Shih-Fu Chang
For long videos, given a paragraph of description where the sentences describe different segments of the video, by matching all sentence-clip pairs, the paragraph and the full video are aligned implicitly.
no code implementations • 16 Apr 2022 • Guangxing Han, Long Chen, Jiawei Ma, Shiyuan Huang, Rama Chellappa, Shih-Fu Chang
Our approach is motivated by the high-level conceptual similarity of (metric-based) meta-learning and prompt-based learning to learn generalizable few-shot and zero-shot object detection models respectively without fine-tuning.
1 code implementation • CVPR 2022 • Guangxing Han, Jiawei Ma, Shiyuan Huang, Long Chen, Shih-Fu Chang
Inspired by the recent work on vision transformers and vision-language transformers, we propose a novel Fully Cross-Transformer based model (FCT) for FSOD by incorporating cross-transformer into both the feature backbone and detection head.
1 code implementation • ICCV 2021 • Guangxing Han, Yicheng He, Shiyuan Huang, Jiawei Ma, Shih-Fu Chang
Few-shot object detection (FSOD) aims to detect never-seen objects using few examples.
no code implementations • IEEE International Conference on Image Processing (ICIP) 2021 • Jiawei Ma, Xiaoyu Tao, Jianxing Ma, Xiaopeng Hong, Yihong Gong
Class Incremental Learning (CIL) is a hot topic in machine learning for CNN models to learn new classes incrementally.
no code implementations • ICCV 2021 • Jiawei Ma, Hanchen Xie, Guangxing Han, Shih-Fu Chang, Aram Galstyan, Wael Abd-Almageed
In this paper, we focus on the design of training strategy to obtain an elemental representation such that the prototype of each novel class can be estimated from a few labeled samples.
2 code implementations • 15 Apr 2021 • Guangxing Han, Shiyuan Huang, Jiawei Ma, Yicheng He, Shih-Fu Chang
To improve the fine-grained few-shot proposal classification, we propose a novel attentive feature alignment method to address the spatial misalignment between the noisy proposals and few-shot classes, thus improving the performance of few-shot object detection.
1 code implementation • CVPR 2022 • Shiyuan Huang, Jiawei Ma, Guangxing Han, Shih-Fu Chang
In this paper, we instead propose task-adaptive negative class envision for FSOR to integrate threshold tuning into the learning process.
no code implementations • NAACL 2021 • Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, Haoran Zhang, Weili Liu, Aabhas Chauhan, Yingjun Guan, Bangzheng Li, Ruisong Li, Xiangchen Song, Yi R. Fung, Heng Ji, Jiawei Han, Shih-Fu Chang, James Pustejovsky, Jasmine Rah, David Liem, Ahmed Elsayed, Martha Palmer, Clare Voss, Cynthia Schneider, Boyan Onyshkevych
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions.
no code implementations • ICCV 2019 • Jiawei Ma, Xiao-Yang Liu, Zheng Shou, Xin Yuan
In this paper, we propose a deep tensor ADMM-Net for video SCI systems that provides high-quality decoding in seconds.
2 code implementations • 23 May 2019 • Jiawei Ma, Zheng Shou, Alireza Zareian, Hassan Mansour, Anthony Vetro, Shih-Fu Chang
In order to jointly capture the self-attention across multiple dimensions, including time, location and the sensor measurements, while maintain low computational complexity, we propose a novel approach called Cross-Dimensional Self-Attention (CDSA) to process each dimension sequentially, yet in an order-independent manner.