no code implementations • 28 Feb 2023 • Srikanth Malla, Yi-Ting Chen
Point cloud data plays an essential role in robotics and self-driving applications.
no code implementations • CVPR 2023 • Yao-Chih Lee, Ji-Ze Genevieve Jang, Yi-Ting Chen, Elizabeth Qiu, Jia-Bin Huang
Temporal consistency is essential for video editing applications.
no code implementations • 2 Jan 2023 • Zihao Xiao, Alan Yuille, Yi-Ting Chen
In this work, we tackle two vital tasks in automated driving systems, i. e., driver intent prediction and risk object identification from egocentric images.
no code implementations • 31 Oct 2022 • I-Chun Chern, Kuo-Hsuan Hung, Yi-Ting Chen, Tassadaq Hussain, Mandar Gogate, Amir Hussain, Yu Tsao, Jen-Cheng Hou
In summary, our results confirm the effectiveness of our proposed model for the AVSS task with proper fine-tuning strategies, demonstrating that multi-modal self-supervised embeddings obtained from AV-HuBERT can be generalized to audio-visual regression tasks.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
1 code implementation • 27 Sep 2022 • Chi-Ming Chung, Yang-Che Tseng, Ya-Ching Hsu, Xiang-Qian Shi, Yun-Hung Hua, Jia-Fong Yeh, Wen-Chin Chen, Yi-Ting Chen, Winston H. Hsu
A spatial AI that can perform complex tasks through visual signals and cooperate with humans is highly anticipated.
no code implementations • 18 Sep 2022 • Kevin Zhang, Mingyang Xie, Maharshi Gor, Yi-Ting Chen, Yvonne Zhou, Christopher A. Metzler
Deep image prior (DIP) is a recently proposed technique for solving imaging inverse problems by fitting the reconstructed images to the output of an untrained convolutional neural network.
no code implementations • 16 Feb 2022 • Huihui Fang, Fei Li, Huazhu Fu, Xu sun, Xingxing Cao, Fengbin Lin, Jaemin Son, Sunho Kim, Gwenole Quellec, Sarah Matta, Sharath M Shankaranarayana, Yi-Ting Chen, Chuen-heng Wang, Nisarg A. Shah, Chia-Yen Lee, Chih-Chung Hsu, Hai Xie, Baiying Lei, Ujjwal Baid, Shubham Innani, Kang Dang, Wenxiu Shi, Ravi Kamble, Nitin Singhal, Ching-Wei Wang, Shih-Chang Lo, José Ignacio Orlando, Hrvoje Bogunović, Xiulan Zhang, Yanwu Xu, iChallenge-AMD study group
The ADAM challenge consisted of four tasks which cover the main aspects of detecting and characterizing AMD from fundus images, including detection of AMD, detection and segmentation of optic disc, localization of fovea, and detection and segmentation of lesions.
no code implementations • 1 Feb 2022 • Jianren Wang, Haiming Gang, Siddharth Ancha, Yi-Ting Chen, David Held
However, these detectors usually require training on large amounts of annotated data that is expensive and time-consuming to collect.
no code implementations • 4 Dec 2021 • Jia-Fong Yeh, Chi-Ming Chung, Hung-Ting Su, Yi-Ting Chen, Winston H. Hsu
(3) Learning from a different expert.
no code implementations • 19 Nov 2021 • Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le
Second, while increasing the dataset size and the model size has been the defacto method to improve the performance of deep learning models like BASIC, the effect of a large contrastive batch size on such contrastive-trained image-text models is not well-understood.
no code implementations • 24 Jun 2021 • Chengxi Li, Stanley H. Chan, Yi-Ting Chen
Identification of high-risk driving situations is generally approached through collision risk estimation or accident pattern recognition.
1 code implementation • 26 May 2021 • Chun-Ta Lu, Yun Zeng, Da-Cheng Juan, Yicheng Fan, Zhe Li, Jan Dlabal, Yi-Ting Chen, Arjun Gopalan, Allan Heydon, Chun-Sung Ferng, Reah Miyara, Ariel Fuxman, Futang Peng, Zhen Li, Tom Duerig, Andrew Tomkins
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchronous fashion across hardware platforms.
2 code implementations • 7 Apr 2021 • Yi-Ting Chen, Jinghao Shi, Zelin Ye, Christoph Mertz, Deva Ramanan, Shu Kong
Object detection with multimodal inputs can improve many safety-critical systems such as autonomous vehicles (AVs).
3 code implementations • 11 Feb 2021 • Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, YunHsuan Sung, Zhen Li, Tom Duerig
In this paper, we leverage a noisy dataset of over one billion image alt-text pairs, obtained without expensive filtering or post-processing steps in the Conceptual Captions dataset.
Ranked #1 on Image Classification on VTAB-1k (using extra training data)
no code implementations • 19 Oct 2020 • Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang
Spatio-temporal action localization is an important problem in computer vision that involves detecting where and when activities occur, and therefore requires modeling of both spatial and temporal features.
1 code implementation • 18 Aug 2020 • Jianren Wang, Siddharth Ancha, Yi-Ting Chen, David Held
Instead, we propose leveraging vast unlabeled datasets by self-supervised metric learning of 3D object trackers, with a focus on data association.
no code implementations • LREC 2020 • Yi-Ting Chen, Hen-Hsen Huang, Hsin-Hsi Chen
In this paper, we collect the conversions from TV series scripts, and annotate emotion and interpersonal relationship labels on each utterance.
no code implementations • 18 Mar 2020 • Hao Zhang, Yi-Ting Chen, Liyao Xiang, Haotian Ma, Jie Shi, Quanshi Zhang
We propose a method to revise the neural network to construct the quaternion-valued neural network (QNN), in order to prevent intermediate-layer features from leaking input information.
no code implementations • 5 Mar 2020 • Chengxi Li, Stanley H. Chan, Yi-Ting Chen
We formulate the task as the cause-effect problem and present a novel two-stage risk object identification framework based on causal inference with the proposed object-level manipulable driving model.
no code implementations • CVPR 2019 • Jinkyu Kim, Teruhisa Misu, Yi-Ting Chen, Ashish Tawari, John Canny
We show that taking advice improves the performance of the end-to-end network, while the network cues on a variety of visual features that are provided by advice.
no code implementations • 20 Sep 2019 • Chengxi Li, Yue Meng, Stanley H. Chan, Yi-Ting Chen
First, we decompose egocentric interactions into ego-thing and ego-stuff interaction, modeled by two GCNs.
no code implementations • 4 Mar 2019 • Abhishek Patil, Srikanth Malla, Haiming Gang, Yi-Ting Chen
Finally, sources of errors are discussed for the development of future algorithms.
1 code implementation • 14 Feb 2019 • Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi
Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering.
Ranked #10 on Image Classification on iNaturalist
no code implementations • 7 Feb 2019 • Ahmed Taha, Yi-Ting Chen, Teruhisa Misu, Abhinav Shrivastava, Larry Davis
We introduce an unsupervised formulation to estimate heteroscedastic uncertainty in retrieval systems.
1 code implementation • 24 Jan 2019 • Ahmed Taha, Yi-Ting Chen, Teruhisa Misu, Abhinav Shrivastava, Larry Davis
We employ triplet loss as a feature embedding regularizer to boost classification performance.
no code implementations • 23 Jan 2019 • Ahmed Taha, Yi-Ting Chen, Xitong Yang, Teruhisa Misu, Larry Davis
We cast visual retrieval as a regression problem by posing triplet loss as a regression loss.
2 code implementations • ICCV 2019 • Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry S. Davis, David J. Crandall
Most work on temporal action detection is formulated as an offline problem, in which the start and end times of actions are determined after the entire video is fully observed.
Ranked #6 on Online Action Detection on TVSeries
no code implementations • CVPR 2018 • Vasili Ramanishka, Yi-Ting Chen, Teruhisa Misu, Kate Saenko
We present the Honda Research Institute Driving Dataset (HDD), a challenging dataset to enable research on learning driver behavior in real-life environments.
no code implementations • 2 Jul 2018 • Athma Narayanan, Yi-Ting Chen, Srikanth Malla
First, predefined driving behaviors are sparse in a naturalistic driving setting.
no code implementations • 16 Jun 2018 • Ahmed Taha, Moustafa Meshry, Xitong Yang, Yi-Ting Chen, Larry Davis
The self-supervised pre-trained weights effectiveness is validated on the action recognition task.
no code implementations • CVPR 2015 • Yi-Ting Chen, Xiaokai Liu, Ming-Hsuan Yang
We present a multi-instance object segmentation algorithm to tackle occlusions.