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Found 24 papers, 5 papers with code
Definition Modelling for Appropriate Specificity
Definition generation techniques aim to generate a definition of a target word or phrase given a context.
JADE: Corpus for Japanese Definition Modelling
This study investigated and released the JADE, a corpus for Japanese definition modelling, which is a technique that automatically generates definitions of a given target word and phrase.
PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
Our proposed framework provides a conditional feature extraction module first to extract the coarse yet effective spatiotemporal dependencies from conditional information as the global context prior.
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
However, accurately modeling distribution and rapidly generating novel molecular graphs remain crucial and challenging goals.
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation
Graph generative models have broad applications in biology, chemistry and social science.
A Geometric-Relational Deep Learning Framework for BIM Object Classification
It can be supplemented using deep learning.
Privileged Prior Information Distillation for Image Matting
Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance.
UnconFuse: Avatar Reconstruction from Unconstrained Images
The report proposes an effective solution about 3D human body reconstruction from multiple unconstrained frames for ECCV 2022 WCPA Challenge: From Face, Body and Fashion to 3D Virtual avatars I (track1: Multi-View Based 3D Human Body Reconstruction).
CrossHuman: Learning Cross-Guidance from Multi-Frame Images for Human Reconstruction
We propose CrossHuman, a novel method that learns cross-guidance from parametric human model and multi-frame RGB images to achieve high-quality 3D human reconstruction.
Personalized Diagnostic Tool for Thyroid Cancer Classification using Multi-view Ultrasound
Furthermore, finding an optimal way to integrate multi-view information also relies on the experience of clinicians and adds further difficulty to accurate diagnosis.
Bridging Mean-Field Games and Normalizing Flows with Trajectory Regularization
In this work, we unravel the connections between MFGs and NFs by contextualizing the training of an NF as solving the MFG.
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.
Situational Perception Guided Image Matting
In this paper, we propose a Situational Perception Guided Image Matting (SPG-IM) method that mitigates subjective bias of matting annotations and captures sufficient situational perception information for better global saliency distilled from the visual-to-textual task.
Structured Local Radiance Fields for Human Avatar Modeling
These local radiance fields not only leverage the flexibility of implicit representation in shape and appearance modeling, but also factorize cloth deformations into skeleton motions, node residual translations and the dynamic detail variations inside each individual radiance field.
Semantic Distillation Guided Salient Object Detection
Most existing CNN-based salient object detection methods can identify local segmentation details like hair and animal fur, but often misinterpret the real saliency due to the lack of global contextual information caused by the subjectiveness of the SOD task and the locality of convolution layers.
Deep Two-Stream Video Inference for Human Body Pose and Shape Estimation
In this paper, we propose a new framework Deep Two-Stream Video Inference for Human Body Pose and Shape Estimation (DTS-VIBE), to generate 3D human pose and mesh from RGB videos.
Ranked #3 on
3D Human Pose Estimation
on MPI-INF-3DHP
(PA-MPJPE metric)
Virtual Multi-Modality Self-Supervised Foreground Matting for Human-Object Interaction
In this paper, we propose a Virtual Multi-modality Foreground Matting (VMFM) method to learn human-object interactive foreground (human and objects interacted with him or her) from a raw RGB image.
$G^3$: Representation Learning and Generation for Geometric Graphs
A geometric graph is a graph equipped with geometric information (i. e., node coordinates).
Surprisingly Popular Algorithm-based Adaptive Euclidean Distance Topology Learning PSO
And then we propose the Surprisingly Popular Algorithm-based Adaptive Euclidean Distance Topology Learning Particle Swarm Optimization (SpadePSO), which uses SPA to guide the search direction of the exploitation sub-population, and analyze the influence of different topologies on SPA.
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution
Specifically, the cell-level search space is designed based on an information distillation mechanism, focusing on the combinations of lightweight operations and aiming to build a more lightweight and accurate SR structure.
Dirac semimetal PdTe2 temperature-dependent quasiparticle dynamics and electron-phonon coupling
Two distinct carrier and coherent phonons relaxation processes were identified in the 5 K - 300 K range.
Materials Science Superconductivity
Learning to Detect Head Movement in Unconstrained Remote Gaze Estimation in the Wild
To better demonstrate the advantage of our methods, we further propose a new benchmark dataset with the most rich distribution of head-gaze combination reflecting real-world scenarios.
An Improved Epsilon Constraint-handling Method in MOEA/D for CMOPs with Large Infeasible Regions
In order to evaluate the performance of MOEA/D-IEpsilon, a new set of CMOPs with two and three objectives is designed, having large infeasible regions (relative to the feasible regions), and they are called LIR-CMOPs.
A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus images
In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images.
