Search Results for author:
Found 17 papers, 5 papers with code
3D Object Detection from Point Cloud via Voting Step Diffusion
In this work, we focus on the distributional properties of point clouds and formulate the voting process as generating new points in the high-density region of the distribution of object centers.
External Knowledge Enhanced 3D Scene Generation from Sketch
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) for generating customized, diverse, and plausible 3D scenes.
Beyond Skeletons: Integrative Latent Mapping for Coherent 4D Sequence Generation
To address this, we propose a novel framework that generates coherent 4D sequences with animation of 3D shapes under given conditions with dynamic evolution of shape and color over time through integrative latent mapping.
Diffusion-Driven Self-Supervised Learning for Shape Reconstruction and Pose Estimation
Furthermore, we introduce a pretrain-to-refine self-supervised training paradigm to train our network.
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation
In this paper, we propose a sketch and text guided probabilistic diffusion model for colored point cloud generation that conditions the denoising process jointly with a hand drawn sketch of the object and its textual description.
DANet: Density Adaptive Convolutional Network with Interactive Attention for 3D Point Clouds
Local features and contextual dependencies are crucial for 3D point cloud analysis.
3D Spatial Multimodal Knowledge Accumulation for Scene Graph Prediction in Point Cloud
In-depth understanding of a 3D scene not only involves locating/recognizing individual objects, but also requires to infer the relationships and interactions among them.
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
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 which is expensive to generate.
Scene Graph Generation: A Comprehensive Survey
In this paper, we provide a comprehensive survey of recent achievements in this field brought about by deep learning techniques.
Learning From Pixel-Level Noisy Label: A New Perspective for Light Field Saliency Detection
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 which is expensive to generate.
A Systematic Collection of Medical Image Datasets for Deep Learning
Thus, as comprehensive as possible, this paper provides a collection of medical image datasets with their associated challenges for deep learning research.
Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud
There are three main challenges in 3D object grounding: to find the main focus in the complex and diverse description; to understand the point cloud scene; and to locate the target object.
Minimum Potential Energy of Point Cloud for Robust Global Registration
Different from the most existing point set registration methods which usually extract the descriptors to find correspondences between point sets, our proposed MPE alignment method is able to handle large scale raw data offset without depending on traditional descriptors extraction, whether for the local or global registration methods.
Relation Graph Network for 3D Object Detection in Point Clouds
Convolutional Neural Networks (CNNs) have emerged as a powerful strategy for most object detection tasks on 2D images.
Point Attention Network for Semantic Segmentation of 3D Point Clouds
We propose a point attention network that learns rich local shape features and their contextual correlations for 3D point cloud semantic segmentation.
Deep Keyframe Detection in Human Action Videos
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.
3D Face Reconstruction from Light Field Images: A Model-free Approach
Reconstructing 3D facial geometry from a single RGB image has recently instigated wide research interest.
