Search Results for author: Zejian yuan

Found 27 papers, 4 papers with code

CONLINE: Complex Code Generation and Refinement with Online Searching and Correctness Testing

no code implementations20 Mar 2024 Xinyi He, Jiaru Zou, Yun Lin, Mengyu Zhou, Shi Han, Zejian yuan, Dongmei Zhang

Large Language Models (LLMs) have revolutionized code generation ability by converting natural language descriptions into executable code.

Code Generation Information Retrieval +1

CoSSegGaussians: Compact and Swift Scene Segmenting 3D Gaussians with Dual Feature Fusion

no code implementations11 Jan 2024 Bin Dou, Tianyu Zhang, Yongjia Ma, Zhaohui Wang, Zejian yuan

We propose Compact and Swift Segmenting 3D Gaussians(CoSSegGaussians), a method for compact 3D-consistent scene segmentation at fast rendering speed with only RGB images input.

Panoptic Segmentation Scene Segmentation +2

Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries

no code implementations21 Dec 2023 Xinyi He, Mengyu Zhou, Xinrun Xu, Xiaojun Ma, Rui Ding, Lun Du, Yan Gao, Ran Jia, Xu Chen, Shi Han, Zejian yuan, Dongmei Zhang

We evaluate five state-of-the-art models using three different metrics and the results show that our benchmark presents introduces considerable challenge in the field of tabular data analysis, paving the way for more advanced research opportunities.

Question Answering

An Efficient Wide-Range Pseudo-3D Vehicle Detection Using A Single Camera

no code implementations15 Sep 2023 Zhupeng Ye, Yinqi Li, Zejian yuan

This paper proposes a novel wide-range Pseudo-3D Vehicle Detection method based on images from a single camera and incorporates efficient learning methods.

PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer

no code implementations29 Aug 2023 Ruijin Liu, Ning Lu, Dapeng Chen, Cheng Li, Zejian yuan, Wei Peng

We present PBFormer, an efficient yet powerful scene text detector that unifies the transformer with a novel text shape representation Polynomial Band (PB).

Head-Tail Cooperative Learning Network for Unbiased Scene Graph Generation

1 code implementation23 Aug 2023 Lei Wang, Zejian yuan, Yao Lu, Badong Chen

We also propose a self-supervised learning approach to enhance the prediction ability of the tail-prefer feature representation branch by constraining tail-prefer predicate features.

Graph Generation Self-Supervised Learning +1

Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry Constraints

1 code implementation31 Dec 2021 Ruijin Liu, Dapeng Chen, Tie Liu, Zhiliang Xiong, Zejian yuan

In this task, the correct camera pose is the key to generating accurate lanes, which can transform an image from perspective-view to the top-view.

3D Lane Detection Autonomous Vehicles +2

Domain Adaptation Gaze Estimation by Embedding with Prediction Consistency

no code implementations15 Nov 2020 Zidong Guo, Zejian yuan, Chong Zhang, Wanchao Chi, Yonggen Ling, Shenghao Zhang

In domain adaption, we design an embedding representation with prediction consistency to ensure that the linear relationship between gaze directions in different domains remains consistent on gaze space and embedding space.

Domain Adaptation Gaze Estimation

End-to-end Lane Shape Prediction with Transformers

2 code implementations9 Nov 2020 Ruijin Liu, Zejian yuan, Tie Liu, Zhiliang Xiong

To tackle these issues, we propose an end-to-end method that directly outputs parameters of a lane shape model, using a network built with a transformer to learn richer structures and context.

Lane Detection

Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation

no code implementations16 Jul 2020 Ziyang Song, Zejian yuan, Chong Zhang, Wanchao Chi, Yonggen Ling, Shenghao Zhang

In recognition-based action interaction, robots' responses to human actions are often pre-designed according to recognized categories and thus stiff.

Action Recognition Data Augmentation +1

Attention-Oriented Action Recognition for Real-Time Human-Robot Interaction

no code implementations2 Jul 2020 Ziyang Song, Ziyi Yin, Zejian yuan, Chong Zhang, Wanchao Chi, Yonggen Ling, Shenghao Zhang

Despite the notable progress made in action recognition tasks, not much work has been done in action recognition specifically for human-robot interaction.

Action Recognition Pose Estimation

Multi-Kernel Correntropy for Robust Learning

no code implementations24 May 2019 Badong Chen, Yuqing Xie, Xin Wang, Zejian yuan, Pengju Ren, Jing Qin

In a recent work, the concept of mixture correntropy (MC) was proposed to improve the learning performance, where the kernel function is a mixture Gaussian kernel, namely a linear combination of several zero-mean Gaussian kernels with different widths.

Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder

no code implementations26 Oct 2018 Zhihao Zhu, Zhan Xue, Zejian yuan

Recent progress on deep learning has made it possible to automatically transform the screenshot of Graphic User Interface (GUI) into code by using the encoder-decoder framework.

Code Generation

Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition

no code implementations23 Oct 2018 Yuanliu Liu, Ang Li, Zejian yuan, Badong Chen, Nanning Zheng

We propose a Consistency-aware Selective Fusion (CSF) to integrate the pairwise orders into a globally consistent order.

Intrinsic Image Decomposition

Color naming guided intrinsic image decomposition

no code implementations23 Oct 2018 Yuanliu Liu, Zejian yuan

In this paper we propose an efficient way of user interaction that users need only to annotate the color composition of the image.

Color Constancy Intrinsic Image Decomposition

Topic-Guided Attention for Image Captioning

1 code implementation10 Jul 2018 Zhihao Zhu, Zhan Xue, Zejian yuan

Attention mechanisms have attracted considerable interest in image captioning because of its powerful performance.

Image Captioning

SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection

no code implementations3 Jul 2018 Ang Li, Zejian yuan

Detecting the occlusion from stereo images or video frames is important to many computer vision applications.

Optical Flow Estimation

Long-term Multi-granularity Deep Framework for Driver Drowsiness Detection

no code implementations8 Jan 2018 Jie Lyu, Zejian yuan, Dapeng Chen

For real-world driver drowsiness detection from videos, the variation of head pose is so large that the existing methods on global face is not capable of extracting effective features, such as looking aside and lowering head.

Learning Fixation Point Strategy for Object Detection and Classification

no code implementations19 Dec 2017 Jie Lyu, Zejian yuan, Dapeng Chen

The network can learn to extract a sequence of local observations with detailed appearance and rough context, instead of sliding windows or convolutions on the entire image.

Classification General Classification +3

Coordinating Multiple Disparity Proposals for Stereo Computation

no code implementations CVPR 2016 Ang Li, Dapeng Chen, Yuanliu liu, Zejian yuan

While great progress has been made in stereo computation over the last decades, large textureless regions remain challenging.

Similarity Learning With Spatial Constraints for Person Re-Identification

no code implementations CVPR 2016 Dapeng Chen, Zejian yuan, Badong Chen, Nanning Zheng

We therefore learn a novel similarity function, which consists of multiple sub-similarity measurements with each taking in charge of a subregion.

Person Re-Identification

Illumination Robust Color Naming via Label Propagation

no code implementations ICCV 2015 Yuanliu liu, Zejian yuan, Badong Chen, Jianru Xue, Nanning Zheng

In this paper we address the problem of inferring the color composition of the intrinsic reflectance of objects, where the shadows and highlights may change the observed color dramatically.

Image Retrieval Retrieval

Saturation-Preserving Specular Reflection Separation

no code implementations CVPR 2015 Yuanliu Liu, Zejian yuan, Nanning Zheng, Yang Wu

Specular reflection generally decreases the saturation of surface colors, which will be possibly confused with other colors that have the same hue but lower saturation.

Similarity Learning on an Explicit Polynomial Kernel Feature Map for Person Re-Identification

no code implementations CVPR 2015 Dapeng Chen, Zejian yuan, Gang Hua, Nanning Zheng, Jingdong Wang

We follow the learning-to-rank methodology and learn a similarity function to maximize the difference between the similarity scores of matched and unmatched images for a same person.

Learning-To-Rank Patch Matching +1

Salient Object Detection: A Discriminative Regional Feature Integration Approach

no code implementations CVPR 2013 Huaizu Jiang, Zejian yuan, Ming-Ming Cheng, Yihong Gong, Nanning Zheng, Jingdong Wang

Our method, which is based on multi-level image segmentation, utilizes the supervised learning approach to map the regional feature vector to a saliency score.

Image Segmentation Object +4

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