Search Results for author: Zulin Wang

Found 15 papers, 9 papers with code

An AFDM-Based Integrated Sensing and Communications

no code implementations29 Aug 2022 Yuanhan Ni, Zulin Wang, Peng Yuan, Qin Huang

This paper considers an affine frequency division multiplexing (AFDM)-based integrated sensing and communications (ISAC) system, where the AFDM waveform is used to simultaneously carry communications information and sense targets.

Blind VQA on 360° Video via Progressively Learning from Pixels, Frames and Video

1 code implementation18 Nov 2021 Li Yang, Mai Xu, Shengxi Li, Yichen Guo, Zulin Wang

When assessing the quality of 360{\textdegree} video, human tends to perceive its quality degradation from the viewport-based spatial distortion of each spherical frame to motion artifact across adjacent frames, ending with the video-level quality score, i. e., a progressive quality assessment paradigm.

Visual Question Answering (VQA)

Removing Rain in Videos: A Large-scale Database and A Two-stream ConvLSTM Approach

no code implementations6 Jun 2019 Tie Liu, Mai Xu, Zulin Wang

In this paper, we establish a large-scale video database for rain removal (LasVR), which consists of 316 rain videos.

Rain Removal

Saliency Prediction on Omnidirectional Images with Generative Adversarial Imitation Learning

no code implementations15 Apr 2019 Mai Xu, Li Yang, Xiaoming Tao, Yiping Duan, Zulin Wang

According to these findings, our SalGAIL approach applies deep reinforcement learning (DRL) to predict the head fixations of one subject, in which GAIL learns the reward of DRL, rather than the traditional human-designed reward.

Imitation Learning Saliency Prediction

MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video

1 code implementation26 Feb 2019 Qunliang Xing, Zhenyu Guan, Mai Xu, Ren Yang, Tie Liu, Zulin Wang

Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video.

Video Enhancement Video Restoration

Understanding and Predicting the Memorability of Outdoor Natural Scenes

2 code implementations9 Oct 2018 Jiaxin Lu, Mai Xu, Ren Yang, Zulin Wang

In particular, we find that the high-level feature of scene category is rather correlated with outdoor natural scene memorability, and the deep features learnt by deep neural network (DNN) are also effective in predicting the memorability scores.

DeepVS: A Deep Learning Based Video Saliency Prediction Approach

1 code implementation ECCV 2018 Lai Jiang, Mai Xu, Tie Liu, Minglang Qiao, Zulin Wang

Hence, an object-to-motion convolutional neural network (OM-CNN) is developed to predict the intra-frame saliency for DeepVS, which is composed of the objectness and motion subnets.

Saliency Prediction Video Saliency Detection +1

What Makes Natural Scene Memorable?

no code implementations27 Aug 2018 Jiaxin Lu, Mai Xu, Ren Yang, Zulin Wang

Recent studies on image memorability have shed light on the visual features that make generic images, object images or face photographs memorable.

Bridge the Gap Between VQA and Human Behavior on Omnidirectional Video: A Large-Scale Dataset and a Deep Learning Model

1 code implementation29 Jul 2018 Chen Li, Mai Xu, Xinzhe Du, Zulin Wang

To fill in the gap between subjective quality and human behavior, this paper proposes a large-scale visual quality assessment (VQA) dataset of omnidirectional video, called VQA-OV, which collects 60 reference sequences and 540 impaired sequences.

Visual Question Answering (VQA)

Multi-Frame Quality Enhancement for Compressed Video

1 code implementation CVPR 2018 Ren Yang, Mai Xu, Zulin Wang, Tianyi Li

In this paper, we investigate that heavy quality fluctuation exists across compressed video frames, and thus low quality frames can be enhanced using the neighboring high quality frames, seen as Multi-Frame Quality Enhancement (MFQE).

Motion Compensation Video Enhancement

Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach

1 code implementation30 Oct 2017 Yuhang Song, Mai Xu, Jianyi Wang, Minglang Qiao, Liangyu Huo, Zulin Wang

Finally, the experiments validate that our approach is effective in both offline and online prediction of HM positions for panoramic video, and that the learned offline-DHP model can improve the performance of online-DHP.

Position reinforcement-learning +1

Enhancing Quality for HEVC Compressed Videos

no code implementations20 Sep 2017 Ren Yang, Mai Xu, Tie Liu, Zulin Wang, Zhenyu Guan

Our experimental results validate that our QE-CNN method is effective in enhancing quality for both I and P frames of HEVC videos.


Reducing Complexity of HEVC: A Deep Learning Approach

1 code implementation19 Sep 2017 Mai Xu, Tianyi Li, Zulin Wang, Xin Deng, Ren Yang, Zhenyu Guan

Therefore, this paper proposes a deep learning approach to predict the CU partition for reducing the HEVC complexity at both intra- and inter-modes, which is based on convolutional neural network (CNN) and long- and short-term memory (LSTM) network.

Predicting Video Saliency with Object-to-Motion CNN and Two-layer Convolutional LSTM

1 code implementation19 Sep 2017 Lai Jiang, Mai Xu, Zulin Wang

We further find from our database that there exists a temporal correlation of human attention with a smooth saliency transition across video frames.

Saliency Prediction Video Saliency Prediction

Learning to Predict Saliency on Face Images

no code implementations ICCV 2015 Mai Xu, Yun Ren, Zulin Wang

For modeling attention on faces and facial features, the proposed method learns the Gaussian mixture model (GMM) distribution from the fixations of eye tracking data as the top-down features for saliency detection of face images.

Saliency Prediction

Cannot find the paper you are looking for? You can Submit a new open access paper.