19 citations · 82 across the 23 of their papers we have counts for
25 papers
FLaTEC: Frequency-Disentangled Latent Triplanes for Efficient Compression of LiDAR Point Clouds
Xiaoge Zhang, Zijie Wu, Mingtao Feng +4
Point cloud compression methods jointly optimize bitrates and reconstruction distortion. However, balancing compression ratio and reconstruction quality is difficult because low-fr…
Controlled Data Rebalancing in Multi-Task Learning for Real-World Image Super-Resolution
Shuchen Lin, Mingtao Feng, Weisheng Dong +4
Real-world image super-resolution (Real-SR) is a challenging problem due to the complex degradation patterns in low-resolution images. Unlike approaches that assume a broadly encom…
PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation
Yong He, Hongshan Yu, Mingtao Feng +5
Diffusion probabilistic models are traditionally used to generate colors at fixed pixel positions in 2D images. Building on this, we extend diffusion models to point cloud semantic…
Extremely low-bitrate Image Compression Semantically Disentangled by LMMs from a Human Perception Perspective
Juan Song, Lijie Yang, Mingtao Feng
It remains a significant challenge to compress images at extremely low bitrate while achieving both semantic consistency and high perceptual quality. Inspired by human progressive…
Multiview Point Cloud Registration Based on Minimum Potential Energy for Free-Form Blade Measurement
Zijie Wu, Yaonan Wang, Yang Mo +5
Point cloud registration is an essential step for free-form blade reconstruction in industrial measurement. Nonetheless, measuring defects of the 3D acquisition system unavoidably…
DiffCom: Decoupled Sparse Priors Guided Diffusion Compression for Point Clouds
Xiaoge Zhang, Zijie Wu, Mehwish Nasim +3
Lossy compression relies on an autoencoder to transform a point cloud into latent points for storage, leaving the inherent redundancy of latent representations unexplored. To reduc…
Referring Human Pose and Mask Estimation in the Wild
Bo Miao, Mingtao Feng, Zijie Wu +3
We introduce Referring Human Pose and Mask Estimation (R-HPM) in the wild, where either a text or positional prompt specifies the person of interest in an image. This new task hold…
High Frequency Matters: Uncertainty Guided Image Compression with Wavelet Diffusion
Juan Song, Jiaxiang He, Lijie Yang +2
Diffusion probabilistic models have recently achieved remarkable success in generating high-quality images. However, balancing high perceptual quality and low distortion remains ch…
Back2Color: Domain-Adaptive Synthetic-to-Real Monocular Depth Estimation for Dynamic Traffic Scenes
Yufan Zhu, Chongzhi Ran, Mingtao Feng +3
Accurate monocular depth estimation is a fundamental component of vision-based perception systems in intelligent transportation applications. Despite recent progress, unsupervised…
3D Object Detection from Point Cloud via Voting Step Diffusion
Haoran Hou, Mingtao Feng, Zijie Wu +4
3D object detection is a fundamental task in scene understanding. Numerous research efforts have been dedicated to better incorporate Hough voting into the 3D object detection pipe…
Diffusion-Driven Self-Supervised Learning for Shape Reconstruction and Pose Estimation
Jingtao Sun, Yaonan Wang, Mingtao Feng +3
Fully-supervised category-level pose estimation aims to determine the 6-DoF poses of unseen instances from known categories, requiring expensive mannual labeling costs. Recently, v…
Soft Masked Transformer for Point Cloud Processing with Skip Attention-Based Upsampling
Yong He, Hongshan Yu, Chaoxu Mu +5
Point cloud processing methods leverage local and global point features %at the feature level to cater to downstream tasks, yet they often overlook the task-level context inherent…
External Knowledge Enhanced 3D Scene Generation from Sketch
Zijie Wu, Mingtao Feng, Yaonan Wang +4
Generating realistic 3D scenes is challenging due to the complexity of room layouts and object geometries.We propose a sketch based knowledge enhanced diffusion architecture (SEK)…
Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation
Qitong Yang, Mingtao Feng, Zijie Wu +4
Directly learning to model 4D content, including shape, color, and motion, is challenging. Existing methods rely on pose priors for motion control, resulting in limited motion dive…
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation
Zijie Wu, Yaonan Wang, Mingtao Feng +2
Diffusion probabilistic models have achieved remarkable success in text guided image generation. However, generating 3D shapes is still challenging due to the lack of sufficient da…
DANet: Density Adaptive Convolutional Network with Interactive Attention for 3D Point Clouds
Yong He, Hongshan Yu, Zhengeng Yang +3
Local features and contextual dependencies are crucial for 3D point cloud analysis. Many works have been devoted to designing better local convolutional kernels that exploit the co…
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
Mingtao Feng, Kendong Liu, Liang Zhang +3
Saliency detection with light field images is becoming attractive given the abundant cues available, however, this comes at the expense of large-scale pixel level annotated data wh…
Scene Graph Generation: A Comprehensive Survey
Guangming Zhu, Liang Zhang, Youliang Jiang +8
Deep learning techniques have led to remarkable breakthroughs in the field of generic object detection and have spawned a lot of scene-understanding tasks in recent years. Scene gr…
A Systematic Collection of Medical Image Datasets for Deep Learning
Johann Li, Guangming Zhu, Cong Hua +11
The astounding success made by artificial intelligence (AI) in healthcare and other fields proves that AI can achieve human-like performance. However, success always comes with cha…
Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud
Mingtao Feng, Zhen Li, Qi Li +6
3D object grounding aims to locate the most relevant target object in a raw point cloud scene based on a free-form language description. Understanding complex and diverse descripti…
Minimum Potential Energy of Point Cloud for Robust Global Registration
Zijie Wu, Yaonan Wang, Qing Zhu +4
In this paper, we propose a novel minimum gravitational potential energy (MPE)-based algorithm for global point set registration. The feature descriptors extraction algorithms have…
Relation Graph Network for 3D Object Detection in Point Clouds
Mingtao Feng, Syed Zulqarnain Gilani, Yaonan Wang +2
Convolutional Neural Networks (CNNs) have emerged as a powerful strategy for most object detection tasks on 2D images. However, their power has not been fully realised for detectin…
Point Attention Network for Semantic Segmentation of 3D Point Clouds
Mingtao Feng, Liang Zhang, Xuefei Lin +2
Convolutional Neural Networks (CNNs) have performed extremely well on data represented by regularly arranged grids such as images. However, directly leveraging the classic convolut…
Deep Keyframe Detection in Human Action Videos
Xiang Yan, Syed Zulqarnain Gilani, Hanlin Qin +3
Detecting representative frames in videos based on human actions is quite challenging because of the combined factors of human pose in action and the background. This paper address…