Search Results for author:
Found 44 papers, 16 papers with code
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.
Definition Modelling for Appropriate Specificity
Definition generation techniques aim to generate a definition of a target word or phrase given a context.
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
To combine these advantages for 3D molecule generation, we propose a foundation model -- NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation.
Multiple-gain Estimation for Running Time of Evolutionary Combinatorial Optimization
The results indicate that the practical running time aligns with the theoretical results, verifying that the multiple-gain model is more general for running-time analysis of evolutionary combinatorial optimization than state-of-the-art methods.
FatesGS: Fast and Accurate Sparse-View Surface Reconstruction using Gaussian Splatting with Depth-Feature Consistency
Recently, Gaussian Splatting has sparked a new trend in the field of computer vision.
Sparis: Neural Implicit Surface Reconstruction of Indoor Scenes from Sparse Views
Specifically, we investigate the impact of monocular priors on sparse scene reconstruction, introducing a novel prior based on inter-image matching information.
Zero-Shot NAS via the Suppression of Local Entropy Decrease
Based on this proof, architectural topologies are utilized to quantify the suppression of local entropy decrease (SED) as a data-free and running-free proxy.
Beyond Filtering: Adaptive Image-Text Quality Enhancement for MLLM Pretraining
A critical factor in training MLLMs is the quality of image-text pairs within multimodal pretraining datasets.
Exploring the Design Space of Visual Context Representation in Video MLLMs
Then, we explore the scaling effects in frame selection and token selection respectively, and fit the corresponding function curve by conducting extensive empirical experiments.
RiboDiffusion: Tertiary Structure-based RNA Inverse Folding with Generative Diffusion Models
A fundamental challenge is to find functional RNA sequences that satisfy given structural constraints, known as the inverse folding problem.
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
Compared to this, editing Large Vision-Language Models (LVLMs) faces extra challenges from diverse data modalities and complicated model components, and data for LVLMs editing are limited.
Reconstructing the Geometry of Random Geometric Graphs
Random geometric graphs are random graph models defined on metric spaces.
Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations
To ensure the proposed parametrization is well-suited for operator learning, we introduce and prove the notion of sampling invariance for our model, establishing its convergence to a continuous operator in the sampling limit.
NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views
To achieve this, we train a neural network to learn a global implicit field from the on-surface points obtained from SfM and then leverage it as a coarse geometric constraint.
Real-time Animation Generation and Control on Rigged Models via Large Language Models
We introduce a novel method for real-time animation control and generation on rigged models using natural language input.
VI-Diff: Unpaired Visible-Infrared Translation Diffusion Model for Single Modality Labeled Visible-Infrared Person Re-identification
In this paper, we propose VI-Diff, a diffusion model that effectively addresses the task of Visible-Infrared person image translation.
LLMR: Real-time Prompting of Interactive Worlds using Large Language Models
We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs.
MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis
In addition, we design an object-level temporal aggregation (OTA) module that can automatically filter low-quality features and efficiently integrate temporal information from multiple frames to improve the accuracy of tumor diagnosis.
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation
To capture the correlation between molecular graphs and geometries in the diffusion process, we develop a Diffusion Graph Transformer to parameterize the data prediction model that recovers the original data from noisy data.
LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar
Existing approaches to animatable NeRF-based head avatars are either built upon face templates or use the expression coefficients of templates as the driving signal.
CloSET: Modeling Clothed Humans on Continuous Surface with Explicit Template Decomposition
In this way, the clothing deformations are disentangled such that the pose-dependent wrinkles can be better learned and applied to unseen poses.
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.
Neural Reconstruction of Relightable Human Model from Monocular Video
In this paper, we introduce a novel self-supervised framework that takes a monocular video of a moving human as input and generates a 3D neural representation capable of being rendered with novel poses under arbitrary lighting conditions.
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
To accomplish these goals, we propose a novel Conditional Diffusion model based on discrete Graph Structures (CDGS) for molecular graph generation.
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 #53 on
3D Human Pose Estimation
on 3DPW
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).
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.
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.
