Search Results for author: Ming Lu

Found 51 papers, 21 papers with code

Towards Backward-Compatible Continual Learning of Image Compression

1 code implementation29 Feb 2024 Zhihao Duan, Ming Lu, Justin Yang, Jiangpeng He, Zhan Ma, Fengqing Zhu

This paper explores the possibility of extending the capability of pre-trained neural image compressors (e. g., adapting to new data or target bitrates) without breaking backward compatibility, the ability to decode bitstreams encoded by the original model.

Continual Learning Image Compression +1

TinyLIC-High efficiency lossy image compression method

no code implementations17 Feb 2024 Gaocheng Ma, Yinfeng Chai, Tianhao Jiang, Ming Lu, Tong Chen

Image compression has been the subject of extensive research for several decades, resulting in the development of well-known standards such as JPEG, JPEG2000, and H. 264/AVC.

Image Compression

Proximity QA: Unleashing the Power of Multi-Modal Large Language Models for Spatial Proximity Analysis

no code implementations31 Jan 2024 Jianing Li, Xi Nan, Ming Lu, Li Du, Shanghang Zhang

To overcome this limitation in MLLMs, we introduce Proximity Question Answering (Proximity QA), a novel framework designed to enable MLLMs to infer the proximity relationship between objects in images.

Multi-Task Learning Question Answering +1

Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding

no code implementations21 Jan 2024 Yichi Zhang, Zhihao Duan, Ming Lu, Dandan Ding, Fengqing Zhu, Zhan Ma

While convolution and self-attention are extensively used in learned image compression (LIC) for transform coding, this paper proposes an alternative called Contextual Clustering based LIC (CLIC) which primarily relies on clustering operations and local attention for correlation characterization and compact representation of an image.

Clustering Image Compression +3

Deep Covariance Alignment for Domain Adaptive Remote Sensing Image Segmentation

1 code implementation9 Jan 2024 Linshan Wu, Ming Lu, Leyuan Fang

Compared with the existing category alignment methods, our CR aims to regularize the correlation between different dimensions of the features and thus performs more robustly when dealing with the divergent category features of imbalanced and inconsistent distributions.

Image Segmentation Segmentation +1

RustNeRF: Robust Neural Radiance Field with Low-Quality Images

no code implementations6 Jan 2024 Mengfei Li, Ming Lu, Xiaofang Li, Shanghang Zhang

First, existing methods assume enough high-quality images are available for training the NeRF model, ignoring real-world image degradation.

Novel View Synthesis

Deep Hierarchical Video Compression

no code implementations12 Dec 2023 Ming Lu, Zhihao Duan, Fengqing Zhu, Zhan Ma

Recently, probabilistic predictive coding that directly models the conditional distribution of latent features across successive frames for temporal redundancy removal has yielded promising results.

Video Compression

MoEC: Mixture of Experts Implicit Neural Compression

no code implementations3 Dec 2023 Jianchen Zhao, Cheng-Ching Tseng, Ming Lu, Ruichuan An, Xiaobao Wei, He Sun, Shanghang Zhang

However, manually designing the partition scheme for a complex scene is very challenging and fails to jointly learn the partition and INRs.

Data Compression

I-MedSAM: Implicit Medical Image Segmentation with Segment Anything

no code implementations28 Nov 2023 Xiaobao Wei, Jiajun Cao, Yizhu Jin, Ming Lu, Guangyu Wang, Shanghang Zhang

In contrast, implicit methods learn continuous representations for segmentation, which is crucial for medical image segmentation.

Image Segmentation Medical Image Segmentation +2

DiffusionTalker: Personalization and Acceleration for Speech-Driven 3D Face Diffuser

no code implementations28 Nov 2023 Peng Chen, Xiaobao Wei, Ming Lu, Yitong Zhu, Naiming Yao, Xingyu Xiao, Hui Chen

To address the above limitations, we propose DiffusionTalker, a diffusion-based method that utilizes contrastive learning to personalize 3D facial animation and knowledge distillation to accelerate 3D animation generation.

3D Face Animation Contrastive Learning +1

Frequency-Aware Re-Parameterization for Over-Fitting Based Image Compression

no code implementations12 Oct 2023 Yun Ye, Yanjie Pan, Qually Jiang, Ming Lu, Xiaoran Fang, Beryl Xu

Over-fitting-based image compression requires weights compactness for compression and fast convergence for practical use, posing challenges for deep convolutional neural networks (CNNs) based methods.

Image Compression Image Restoration

NOC: High-Quality Neural Object Cloning with 3D Lifting of Segment Anything

no code implementations22 Sep 2023 Xiaobao Wei, Renrui Zhang, Jiarui Wu, Jiaming Liu, Ming Lu, Yandong Guo, Shanghang Zhang

Firstly, to separate the target object from the scene, we propose a novel strategy to lift the multi-view 2D segmentation masks of SAM into a unified 3D variation field.

3D Object Reconstruction Object

Channel prior convolutional attention for medical image segmentation

1 code implementation8 Jun 2023 Hejun Huang, Zuguo Chen, Ying Zou, Ming Lu, Chaoyang Chen

An efficient Channel Prior Convolutional Attention (CPCA) method is proposed in this paper, supporting the dynamic distribution of attention weights in both channel and spatial dimensions.

Image Segmentation Medical Image Segmentation +2

ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation

1 code implementation7 Jun 2023 Jiaming Liu, Senqiao Yang, Peidong Jia, Renrui Zhang, Ming Lu, Yandong Guo, Wei Xue, Shanghang Zhang

Note that, our method can be regarded as a novel transfer paradigm for large-scale models, delivering promising results in adaptation to continually changing distributions.

Test-time Adaptation

CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large Input

1 code implementation CVPR 2023 Senmao Tian, Ming Lu, Jiaming Liu, Yandong Guo, Yurong Chen, Shunli Zhang

Therefore, we design a strategy to build an Edge-to-Bit lookup table that maps the edge score of a patch to the bit of each layer during inference.

Image Super-Resolution Quantization

A Comprehensive Comparison of Projections in Omnidirectional Super-Resolution

no code implementations13 Apr 2023 Huicheng Pi, Senmao Tian, Ming Lu, Jiaming Liu, Yandong Guo, Shunli Zhang

In these works, omnidirectional frames are projected from the 3D sphere to a 2D plane by Equi-Rectangular Projection (ERP).

Super-Resolution

MoWE: Mixture of Weather Experts for Multiple Adverse Weather Removal

no code implementations24 Mar 2023 Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, Shanghang Zhang

Our MoWE achieves SOTA performance in upstream task on the proposed dataset and two public datasets, i. e. All-Weather and Rain/Fog-Cityscapes, and also have better perceptual results in downstream segmentation task compared to other methods.

Autonomous Driving Rain Removal

QARV: Quantization-Aware ResNet VAE for Lossy Image Compression

2 code implementations16 Feb 2023 Zhihao Duan, Ming Lu, Jack Ma, Yuning Huang, Zhan Ma, Fengqing Zhu

This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications.

Image Compression Quantization

Efficient Visual Computing with Camera RAW Snapshots

1 code implementation15 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).

Autonomous Driving Image Compression +2

BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks

no code implementations CVPR 2023 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.

3D Object Detection Autonomous Driving +1

BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection

no code implementations30 Nov 2022 Jiaming Liu, Rongyu Zhang, Xiaoqi Li, Xiaowei Chi, Zehui Chen, Ming Lu, Yandong Guo, Shanghang Zhang

In this paper, we propose a Multi-space Alignment Teacher-Student (MATS) framework to ease the domain shift accumulation, which consists of a Depth-Aware Teacher (DAT) and a Geometric-space Aligned Student (GAS) model.

3D Object Detection Autonomous Driving +4

Rate-Distortion Optimized Post-Training Quantization for Learned Image Compression

no code implementations5 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 improves decoding consistency for interoperability and reduces space-time complexity for implementation.

Image Classification Image Compression +2

Complementary consistency semi-supervised learning for 3D left atrial image segmentation

1 code implementation4 Oct 2022 Hejun Huang, Zuguo Chen, Chaoyang Chen, Ming Lu, Ying Zou

A network based on complementary consistency training, called CC-Net, has been proposed for semi-supervised left atrium image segmentation.

Image Segmentation Segmentation +1

Lossy Image Compression with Quantized Hierarchical VAEs

2 code implementations27 Aug 2022 Zhihao Duan, Ming Lu, Zhan Ma, Fengqing Zhu

Recent research has shown a strong theoretical connection between variational autoencoders (VAEs) and the rate-distortion theory.

Image Compression Quantization

Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer

1 code implementation26 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.

Autonomous Driving Depth Estimation +2

Uncertainty Guided Depth Fusion for Spike Camera

no code implementations26 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.

Autonomous Driving Stereo Depth Estimation

Efficient Meta-Tuning for Content-aware Neural Video Delivery

1 code implementation20 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.

Super-Resolution

Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation

1 code implementation19 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.

High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation

1 code implementation25 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.

Vocal Bursts Intensity Prediction

Adaptive Patch Exiting for Scalable Single Image Super-Resolution

1 code implementation22 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.

Image Super-Resolution

Opening the Black Box of Learned Image Coders

no code implementations26 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.

NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery

no code implementations10 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).

SamplingAug: On the Importance of Patch Sampling Augmentation for Single Image Super-Resolution

1 code implementation30 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.

Data Augmentation Image Super-Resolution

Transformer-based Image Compression

no code implementations12 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.

Image Compression Image Reconstruction

End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation

no code implementations5 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.

Motion Compensation MS-SSIM +3

Contextual Graph Reasoning Networks

no code implementations1 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.

2D Human Pose Estimation Instance Segmentation +4

Decomposition, Compression, and Synthesis (DCS)-based Video Coding: A Neural Exploration via Resolution-Adaptive Learning

no code implementations1 Dec 2020 Ming Lu, Tong Chen, Dandan Ding, Fengqing Zhu, Zhan Ma

Inspired by the facts that retinal cells actually segregate the visual scene into different attributes (e. g., spatial details, temporal motion) for respective neuronal processing, we propose to first decompose the input video into respective spatial texture frames (STF) at its native spatial resolution that preserve the rich spatial details, and the other temporal motion frames (TMF) at a lower spatial resolution that retain the motion smoothness; then compress them together using any popular video coder; and finally synthesize decoded STFs and TMFs for high-fidelity video reconstruction at the same resolution as its native input.

Motion Compensation Super-Resolution +2

Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model

no code implementations9 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.

Motion Compensation MS-SSIM +2

Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

no code implementations13 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.

Optical Flow Estimation Video Compression

A Closed-form Solution to Universal Style Transfer

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.

Style Transfer

Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications

no code implementations3 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.

Video Compression

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