Search Results for author:
Found 26 papers, 11 papers with code
LPSNet: End-to-End Human Pose and Shape Estimation with Lensless Imaging
Human pose and shape (HPS) estimation with lensless imaging is not only beneficial to privacy protection but also can be used in covert surveillance scenarios due to the small size and simple structure of this device.
EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling
We propose EMAGE, a framework to generate full-body human gestures from audio and masked gestures, encompassing facial, local body, hands, and global movements.
Ranked #1 on
3D Face Animation
on BEAT2
Distilling Autoregressive Models to Obtain High-Performance Non-Autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed
To the best of our knowledge, this study is first-of-its-kind to obtain NAR VRP solvers from AR ones through knowledge distillation.
INeAT: Iterative Neural Adaptive Tomography
Here, we propose a neural rendering method for CT reconstruction, named Iterative Neural Adaptive Tomography (INeAT), which incorporates iterative posture optimization to effectively counteract the influence of posture perturbations in data, particularly in cases involving significant posture variations.
Content Significance Distribution of Sub-Text Blocks in Articles and Its Application to Article-Organization Assessment
We explore how to capture the significance of a sub-text block in an article and how it may be used for text mining tasks.
On the Opportunities of Green Computing: A Survey
To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
PC-bzip2: a phase-space continuity enhanced lossless compression algorithm for light field microscopy data
Moreover, by introducing the temporal continuity, our method shows the superior compression ratio on time series data of zebrafish blood vessels.
Tracking Anything in Heart All at Once
Myocardial motion tracking stands as an essential clinical tool in the prevention and detection of Cardiovascular Diseases (CVDs), the foremost cause of death globally.
Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems
The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem with broad real-world applications.
CDIDN: A Registration Model with High Deformation Impedance Capability for Long-Term Tracking of Pulmonary Lesion Dynamics
In this paper, we propose a novel registration model called Cascade-Dilation Inter-Layer Differential Network (CDIDN), which exhibits both high deformation impedance capability (DIC) and accuracy.
Disorder-invariant Implicit Neural Representation
However, the expressive power of INR is limited by the spectral bias in the network training.
Shape-Aware Fine-Grained Classification of Erythroid Cells
BMEC contains 5, 666 images of individual erythroid cells, each of which is extracted from the bone marrow erythroid cell smears and professionally annotated to one of the four types of erythroid cells.
DINER: Disorder-Invariant Implicit Neural Representation
Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problems.
BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis
Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned on multi-modal data is still an unsolved problem due to the lack of available datasets, models and standard evaluation metrics.
Ranked #1 on
Gesture Generation
on BEAT
Contextual Networks and Unsupervised Ranking of Sentences
We construct a contextual network to represent a document with syntactic and semantic relations between word-sentence pairs, based on which we devise an unsupervised algorithm called CNATAR (Contextual Network And Text Analysis Rank) to score sentences, and rank them through a bi-objective 0-1 knapsack maximization problem over topic analysis and sentence scores.
VDPC: Variational Density Peak Clustering Algorithm
Furthermore, we divide all data points into different levels according to their local density and propose a unified clustering framework by combining the advantages of both DPC and DBSCAN.
Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO
While many Particle Swarm Optimization (PSO) algorithms only use fitness to assess the performance of particles, in this work, we adopt Surprisingly Popular Algorithm (SPA) as a complementary metric in addition to fitness.
Neural Architecture Search based on Cartesian Genetic Programming Coding Method
To evolve the architectures under the framework of CGP, the operations such as convolution are identified as the types of function nodes of CGP, and the evolutionary operations are designed based on Evolutionary Strategy.
Learning to Shift Attention for Motion Generation
For multiple modes, we suggest to learn local latent representations of motion trajectories with a density estimation method based on real-valued non-volume preserving (RealNVP) transformations that provides a set of powerful, stably invertible, and learnable transformations.
Quantum Chaos is Quantum
This result implies the impossibility of simulating quantum chaos on a classical computer.
Quantum Physics
Quantum scrambling with classical shadows
Quantum dynamics is of fundamental interest and has implications in quantum information processing.
Quantum Physics
Deep Learning Analysis and Age Prediction from Shoeprints
We collected 100, 000 shoeprints of subjects ranging from 7 to 80 years old and used the data to develop a deep learning end-to-end model ShoeNet to analyze age-related patterns and predict age.
Crossed-Time Delay Neural Network for Speaker Recognition
Time Delay Neural Network (TDNN) is a well-performing structure for DNN-based speaker recognition systems.
Learning Compliance Adaptation in Contact-Rich Manipulation
Compliant robot behavior is crucial for the realization of contact-rich manipulation tasks.
Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets
We release two artificial datasets, Simulated Flying Shapes and Simulated Planar Manipulator that allow to test the learning ability of video processing systems.
Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution
We present a novel deep neural network architecture for representing robot experiences in an episodic-like memory which facilitates encoding, recalling, and predicting action experiences.
