Search Results for author: Ke Yang

Found 23 papers, 7 papers with code

Generic Dependency Modeling for Multi-Party Conversation

1 code implementation21 Feb 2023 Weizhou Shen, Xiaojun Quan, Ke Yang

To model the dependencies between utterances in multi-party conversations, we propose a simple and generic framework based on the dependency parsing results of utterances.

Dependency Parsing

ADEPT: A DEbiasing PrompT Framework

1 code implementation10 Nov 2022 Ke Yang, Charles Yu, Yi Fung, Manling Li, Heng Ji

Despite this, relatively few efforts have been made to debias PLMs by prompt tuning with continuous prompts compared to its discrete counterpart.

Language Modelling Word Embeddings

WITT: A Wireless Image Transmission Transformer for Semantic Communications

1 code implementation2 Nov 2022 Ke Yang, Sixian Wang, Jincheng Dai, Kailin Tan, Kai Niu, Ping Zhang

In this paper, we aim to redesign the vision Transformer (ViT) as a new backbone to realize semantic image transmission, termed wireless image transmission transformer (WITT).

Image Classification

Brand Celebrity Matching Model Based on Natural Language Processing

no code implementations18 Aug 2022 Heming Yang, Ke Yang, Erhan Zhang

What's more, to our best knowledge, the proposed BCM model is the first work on using NLP to solve endorsement issues, so it can provide some novel research ideas and methodologies for the following works.

Distributed Image Transmission using Deep Joint Source-Channel Coding

no code implementations25 Jan 2022 Sixian Wang, Ke Yang, Jincheng Dai, Kai Niu

In particular, we consider a pair of images captured by two cameras with probably overlapping fields of view transmitted over wireless channels and reconstructed in the center node.

Fairness in Ranking: A Survey

no code implementations25 Mar 2021 Meike Zehlike, Ke Yang, Julia Stoyanovich

In this survey, we describe four classification frameworks for fairness-enhancing interventions, along which we relate the technical methods surveyed in this paper, discuss evaluation datasets, and present technical work on fairness in score-based ranking.

Fairness Information Retrieval +4

Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

no code implementations5 Nov 2020 Xuanzhao Wang, Zhengping Che, Bo Jiang, Ning Xiao, Ke Yang, Jian Tang, Jieping Ye, Jingyu Wang, Qi Qi

In this paper, we propose a novel and robust unsupervised video anomaly detection method by frame prediction with proper design which is more in line with the characteristics of surveillance videos.

Anomaly Detection Video Anomaly Detection

Two-dimensional ferromagnetic semiconductor VBr3 with tunable anisotropy

no code implementations20 Aug 2020 Lu Liu, Ke Yang, Guangyu Wang, Hua Wu

Two-dimensional (2D) ferromagnets (FMs) have attracted widespread attention due to their prospects in spintronic applications.

Materials Science Strongly Correlated Electrons

Causal intersectionality for fair ranking

2 code implementations15 Jun 2020 Ke Yang, Joshua R. Loftus, Julia Stoyanovich

In this paper we propose a causal modeling approach to intersectional fairness, and a flexible, task-specific method for computing intersectionally fair rankings.

Causal Inference Fairness

Is the four-dimensional novel EGB theory equivalent to its regularized counterpart in a cylindrically symmetric spacetime?

no code implementations14 Jun 2020 Zi-Chao Lin, Ke Yang, Shao-Wen Wei, Yong-Qiang Wang, Yu-Xiao Liu

Thus it is expected that the novel four-dimensional EGB theory is equivalent to its regularized version.

General Relativity and Quantum Cosmology High Energy Physics - Theory

Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

1 code implementation18 Mar 2020 Weikai Tan, Nannan Qin, Lingfei Ma, Ying Li, Jing Du, Guorong Cai, Ke Yang, Jonathan Li

Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definition (HD) mapping.

Autonomous Driving Scene Understanding +1

Towards Precise End-to-end Weakly Supervised Object Detection Network

1 code implementation ICCV 2019 Ke Yang, Dongsheng Li, Yong Dou

It is challenging for weakly supervised object detection network to precisely predict the positions of the objects, since there are no instance-level category annotations.

Multiple Instance Learning object-detection +2

Balanced Ranking with Diversity Constraints

no code implementations4 Jun 2019 Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich

Many set selection and ranking algorithms have recently been enhanced with diversity constraints that aim to explicitly increase representation of historically disadvantaged populations, or to improve the overall representativeness of the selected set.


IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition

no code implementations26 Feb 2019 Ke Yang, Peng Qiao, Dongsheng Li, Yong Dou

Focusing on discriminate spatiotemporal feature learning, we propose Information Fused Temporal Transformation Network (IF-TTN) for action recognition on top of popular Temporal Segment Network (TSN) framework.

Action Recognition Optical Flow Estimation +1

Exploring Frame Segmentation Networks for Temporal Action Localization

no code implementations14 Feb 2019 Ke Yang, Xiaolong Shen, Peng Qiao, Shijie Li, Dongsheng Li, Yong Dou

The proposed FSN can make dense predictions at frame-level for a video clip using both spatial and temporal context information.

Temporal Action Localization

Exploring Temporal Preservation Networks for Precise Temporal Action Localization

no code implementations10 Aug 2017 Ke Yang, Peng Qiao, Dongsheng Li, Shaohe Lv, Yong Dou

A newly proposed work exploits Convolutional-Deconvolutional-Convolutional (CDC) filters to upsample the predictions of 3D ConvNets, making it possible to perform per-frame action predictions and achieving promising performance in terms of temporal action localization.

Temporal Action Localization Temporal Localization

Weakly supervised object detection using pseudo-strong labels

no code implementations16 Jul 2016 Ke Yang, Dongsheng Li, Yong Dou, Shaohe Lv, Qiang Wang

Object detection is an import task of computer vision. A variety of methods have been proposed, but methods using the weak labels still do not have a satisfactory result. In this paper, we propose a new framework that using the weakly supervised method's output as the pseudo-strong labels to train a strongly supervised model. One weakly supervised method is treated as black-box to generate class-specific bounding boxes on train dataset. A de-noise method is then applied to the noisy bounding boxes. Then the de-noised pseudo-strong labels are used to train a strongly object detection network. The whole framework is still weakly supervised because the entire process only uses the image-level labels. The experiment results on PASCAL VOC 2007 prove the validity of our framework, and we get result 43. 4% on mean average precision compared to 39. 5% of the previous best result and 34. 5% of the initial method, respectively. And this frame work is simple and distinct, and is promising to be applied to other method easily.

object-detection Weakly Supervised Object Detection

Relative distance features for gait recognition with Kinect

no code implementations18 May 2016 Ke Yang, Yong Dou, Shaohe Lv, Fei Zhang, Qi Lv

This study focuses on human recognition with gait feature obtained by Kinect and shows that gait feature can effectively distinguish from different human beings through a novel representation -- relative distance-based gait features.

Gait Recognition

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