1 code implementation • 16 Feb 2023 • Zhihao Duan, Ming Lu, Jack Ma, Zhan Ma, Fengqing Zhu
We consider the problem of lossy image compression, a fundamental problem in both information theory and many real-world applications.
1 code implementation • 15 Dec 2022 • Zhihao LI, Ming Lu, Xu Zhang, Xin Feng, M. Salman Asif, Zhan Ma
Conventional cameras capture image irradiance on a sensor and convert it to RGB images using an image signal processor (ISP).
no code implementations • 2 Dec 2022 • Xiaowei Chi, Jiaming Liu, Ming Lu, Rongyu Zhang, Zhaoqing Wang, Yandong Guo, Shanghang Zhang
In order to find them, we further propose a LiDAR-guided sampling strategy to leverage the statistical distribution of LiDAR to determine the heights of local slices.
no code implementations • 1 Dec 2022 • Jianing Li, Ming Lu, Jiaming Liu, Yandong Guo, Li Du, Shanghang Zhang
In this paper, we propose a unified framework named BEV-LGKD to transfer the knowledge in the teacher-student manner.
no code implementations • 30 Nov 2022 • Jiaming Liu, Rongyu Zhang, Xiaowei Chi, Xiaoqi Li, Ming Lu, Yandong Guo, Shanghang Zhang
Vision-Centric Bird-Eye-View (BEV) perception has shown promising potential and attracted increasing attention in autonomous driving.
no code implementations • 5 Nov 2022 • Junqi Shi, Ming Lu, Zhan Ma
Quantizing a floating-point neural network to its fixed-point representation is crucial for Learned Image Compression (LIC) because it assures the decoding consistency for interoperability and reduces space-time complexity for implementation.
1 code implementation • 4 Oct 2022 • Hejun Huang, Zuguo Chen, Chaoyang Chen, Ming Lu, Ying Zou
The inter-model perturbation is formed between the main model and the auxiliary model to form complementary consistency training.
1 code implementation • 27 Aug 2022 • Zhihao Duan, Ming Lu, Zhan Ma, Fengqing Zhu
Recent work has shown a strong theoretical connection between variational autoencoders (VAEs) and the rate distortion theory.
1 code implementation • 26 Aug 2022 • Jiaming Liu, Qizhe Zhang, Jianing Li, Ming Lu, Tiejun Huang, Shanghang Zhang
Neuromorphic spike data, an upcoming modality with high temporal resolution, has shown promising potential in real-world applications due to its inherent advantage to overcome high-velocity motion blur.
no code implementations • 26 Aug 2022 • Jianing Li, Jiaming Liu, Xiaobao Wei, Jiyuan Zhang, Ming Lu, Lei Ma, Li Du, Tiejun Huang, Shanghang Zhang
In this paper, we propose a novel Uncertainty-Guided Depth Fusion (UGDF) framework to fuse the predictions of monocular and stereo depth estimation networks for spike camera.
1 code implementation • 20 Jul 2022 • Xiaoqi Li, Jiaming Liu, Shizun Wang, Cheng Lyu, Ming Lu, Yurong Chen, Anbang Yao, Yandong Guo, Shanghang Zhang
Our method significantly reduces the computational cost and achieves even better performance, paving the way for applying neural video delivery techniques to practical applications.
1 code implementation • 19 Jul 2022 • Jingwang Ling, Zhibo Wang, Ming Lu, Quan Wang, Chen Qian, Feng Xu
Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details.
1 code implementation • 25 Apr 2022 • Ming Lu, Fangdong Chen, ShiLiang Pu, Zhan Ma
To this end, Integrated Convolution and Self-Attention (ICSA) unit is first proposed to form a content-adaptive transform to characterize and embed neighborhood information dynamically of any input.
1 code implementation • 22 Mar 2022 • Shizun Wang, Jiaming Liu, Kaixin Chen, Xiaoqi Li, Ming Lu, Yandong Guo
Once the incremental capacity is below the threshold, the patch can exit at the specific layer.
no code implementations • 26 Feb 2022 • Zhihao Duan, Ming Lu, Zhan Ma, Fengqing Zhu
End-to-end learned lossy image coders (LICs), as opposed to hand-crafted image codecs, have shown increasing superiority in terms of the rate-distortion performance.
no code implementations • 10 Jan 2022 • Ming Lu, Leyuan Fang, Muxing Li, Bob Zhang, Yi Zhang, Pedram Ghamisi
Therefore, we study how to utilize point labels to extract water bodies and propose a novel method called the neighbor feature aggregation network (NFANet).
1 code implementation • 30 Nov 2021 • Shizun Wang, Ming Lu, Kaixin Chen, Jiaming Liu, Xiaoqi Li, Chuang Zhang, Ming Wu
However, existing methods mostly train the DNNs on uniformly sampled LR-HR patch pairs, which makes them fail to fully exploit informative patches within the image.
no code implementations • 12 Nov 2021 • Ming Lu, Peiyao Guo, Huiqing Shi, Chuntong Cao, Zhan Ma
A Transformer-based Image Compression (TIC) approach is developed which reuses the canonical variational autoencoder (VAE) architecture with paired main and hyper encoder-decoders.
1 code implementation • ICCV 2021 • Jiaming Liu, Ming Lu, Kaixin Chen, Xiaoqi Li, Shizun Wang, Zhaoqing Wang, Enhua Wu, Yurong Chen, Chuang Zhang, Ming Wu
Internet video delivery has undergone a tremendous explosion of growth over the past few years.
1 code implementation • 11 Aug 2021 • Yikai Wang, Fuchun Sun, Ming Lu, Anbang Yao
We propose a compact and effective framework to fuse multimodal features at multiple layers in a single network.
Ranked #22 on Semantic Segmentation on NYU Depth v2
no code implementations • 5 Aug 2021 • Haojie Liu, Ming Lu, Zhiqi Chen, Xun Cao, Zhan Ma, Yao Wang
We further design a one-to-many decoder pipeline to generate multiple predictions from the CSTR, including vector-based resampling, adaptive kernel-based resampling, compensation mode selection maps and texture enhancements, and combines them adaptively to achieve more accurate inter prediction.
1 code implementation • 21 Apr 2021 • Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng Li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, XiaoYu Zhang, Linjie Zhou, Sixin Lin, Ru Wang
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.
no code implementations • 1 Jan 2021 • Zhaoqing Wang, Jiaming Liu, Yangyuxuan Kang, Mingming Gong, Chuang Zhang, Ming Lu, Ming Wu
Graph Reasoning has shown great potential recently in modeling long-range dependencies, which are crucial for various computer vision tasks.
no code implementations • 1 Dec 2020 • Ming Lu, Tong Chen, zhenyu Dai, Dong Wang, Dandan Ding, Zhan Ma
This paper proposes a decoder-side Cross Resolution Synthesis (CRS) module to pursue better compression efficiency beyond the latest Versatile Video Coding (VVC), where we encode intra frames at original high resolution (HR), compress inter frames at a lower resolution (LR), and then super-resolve decoded LR inter frames with the help from preceding HR intra and neighboring LR inter frames.
no code implementations • 17 Oct 2020 • Yunchao Wei, Shuai Zheng, Ming-Ming Cheng, Hang Zhao, LiWei Wang, Errui Ding, Yi Yang, Antonio Torralba, Ting Liu, Guolei Sun, Wenguan Wang, Luc van Gool, Wonho Bae, Junhyug Noh, Jinhwan Seo, Gunhee Kim, Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang, Chuangchuang Tan, Tao Ruan, Guanghua Gu, Shikui Wei, Yao Zhao, Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych, Zhendong Wang, Zhenyuan Chen, Chen Gong, Huanqing Yan, Jun He
The purpose of the Learning from Imperfect Data (LID) workshop is to inspire and facilitate the research in developing novel approaches that would harness the imperfect data and improve the data-efficiency during training.
no code implementations • 9 Jul 2020 • Haojie Liu, Ming Lu, Zhan Ma, Fan Wang, Zhihuang Xie, Xun Cao, Yao Wang
Over the past two decades, traditional block-based video coding has made remarkable progress and spawned a series of well-known standards such as MPEG-4, H. 264/AVC and H. 265/HEVC.
no code implementations • 13 Dec 2019 • Haojie Liu, Han Shen, Lichao Huang, Ming Lu, Tong Chen, Zhan Ma
Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency.
2 code implementations • ICCV 2019 • Ming Lu, Hao Zhao, Anbang Yao, Yurong Chen, Feng Xu, Li Zhang
Although plenty of methods have been proposed, a theoretical analysis of feature transform is still missing.
no code implementations • 3 May 2019 • Ming Lu, Ming Cheng, Yiling Xu, ShiLiang Pu, Qiu Shen, Zhan Ma
Networked video applications, e. g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth.
no code implementations • 19 Apr 2019 • Yiwen Guo, Ming Lu, WangMeng Zuo, Chang-Shui Zhang, Yurong Chen
Convolutional neural networks have been proven effective in a variety of image restoration tasks.
no code implementations • ICCV 2017 • Ming Lu, Hao Zhao, Anbang Yao, Feng Xu, Yurong Chen, Li Zhang
Our method decomposes the semantic style transfer problem into feature reconstruction part and feature decoder part.
1 code implementation • CVPR 2017 • Tao Kong, Fuchun Sun, Anbang Yao, Huaping Liu, Ming Lu, Yurong Chen
To address (a), we design the reverse connection, which enables the network to detect objects on multi-levels of CNNs.
no code implementations • CVPR 2017 • Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang
In this paper, we propose an alternative method to estimate room layouts of cluttered indoor scenes.