1 code implementation • EMNLP 2021 • Yuji Zhang, Yubo Zhang, Chunpu Xu, Jing Li, Ziyan Jiang, Baolin Peng
It is hypothesized that one’s interests in a hashtag are related with what they said before (user history) and the existing posts present the hashtag (hashtag contexts).
no code implementations • 10 Oct 2023 • Yubo Zhang, Yanfang Liu, Xinxin Fan, Yunfeng Lu
However, existing code search methods still suffer from two performance constraints: inadequate semantic representation and the semantic gap between natural language (NL) and programming language (PL).
no code implementations • 13 Mar 2023 • Shuxian Wang, Yubo Zhang, Sarah K. McGill, Julian G. Rosenman, Jan-Michael Frahm, Soumyadip Sengupta, Stephen M. Pizer
Reconstructing a 3D surface from colonoscopy video is challenging due to illumination and reflectivity variation in the video frame that can cause defective shape predictions.
no code implementations • 3 Nov 2022 • Yubo Zhang, Xingxing Zhang, Xun Wang, Si-Qing Chen, Furu Wei
In this paper, we propose Lotus (shorthand for Latent Prompt Tuning for Summarization), which is a single model that can be applied in both controlled and uncontrolled (without control signals) modes.
no code implementations • 31 Oct 2022 • Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang
In this paper, we present a unified end-to-end differentiable framework for multi-view, multi-frame hand tracking that directly predicts 3D hand pose in world space.
no code implementations • 22 Apr 2022 • Yubo Zhang, Feiyang Niu, Qing Ping, Govind Thattai
To solve video-and-language grounding tasks, the key is for the network to understand the connection between the two modalities.
1 code implementation • ACL 2022 • Xiaoxin Lu, Yubo Zhang, Jing Li, Shi Zong
Huge volumes of patient queries are daily generated on online health forums, rendering manual doctor allocation a labor-intensive task.
no code implementations • 19 Nov 2021 • Yubo Zhang, Jan-Michael Frahm, Samuel Ehrenstein, Sarah K. McGill, Julian G. Rosenman, Shuxian Wang, Stephen M. Pizer
Aiming to fundamentally improve the depth estimation quality for colonoscopy 3D reconstruction, in this work we have designed a set of training losses to deal with the special challenges of colonoscopy data.
no code implementations • 29 Sep 2021 • Xueqi Ma, Yubo Zhang, Weifeng Liu, Yue Gao
Based on the frequency principle on GNNs, we present a novel powerful GNNs framework, Multi-Scale Frequency Enhanced Graph Neural Networks (MSF-GNNs) which considers multi-scale representations from wavelet decomposition.
no code implementations • 18 Mar 2021 • Yubo Zhang, Shuxian Wang, Ruibin Ma, Sarah K. McGill, Julian G. Rosenman, Stephen M. Pizer
In this work we focus on the lighting problem in colonoscopy videos.
no code implementations • CVPR 2021 • Peirong Liu, Lin Tian, Yubo Zhang, Stephen R. Aylward, Yueh Z. Lee, Marc Niethammer
To help with identifiability, we develop an advection-diffusion simulator which allows pre-training of our model by supervised learning using the velocity and diffusion tensor fields.
no code implementations • 10 Sep 2020 • Hengrui Wang, Yubo Zhang, Mingzhi Chen, Tong Yang
We first divide objects into a great many tiny clusters.
1 code implementation • 6 May 2020 • Yubo Zhang, Hao Tan, Mohit Bansal
Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions, explore the given environments, and reach the desired target locations.
no code implementations • 21 May 2019 • Hengyu Zhao, Yubo Zhang, Pingfan Meng, Hui Shi, Li Erran Li, Tiancheng Lou, Jishen Zhao
To address this issue, we propose a `safety score' as a primary metric for measuring the level of safety in AV computing system design.
no code implementations • 29 Apr 2019 • Yubo Zhang, Pavel Tokmakov, Martial Hebert, Cordelia Schmid
In this work we study the problem of action detection in a highly-imbalanced dataset.
no code implementations • CVPR 2019 • Yubo Zhang, Pavel Tokmakov, Martial Hebert, Cordelia Schmid
A dominant paradigm for learning-based approaches in computer vision is training generic models, such as ResNet for image recognition, or I3D for video understanding, on large datasets and allowing them to discover the optimal representation for the problem at hand.
no code implementations • 9 Dec 2016 • Yubo Zhang, Vishnu Naresh Boddeti, Kris M. Kitani
Concretely, our approach uses two convolutional neural networks: (1) a gesture network that uses pre-defined motion information to detect the hand region; and (2) an appearance network that learns a person specific model of the hand region based on the output of the gesture network.