7 citations · 28 across the 26 of their papers we have counts for
31 papers
High-fidelity Three-Dimensional Flow Field Reconstruction Driven by Turbulent Fluid Dynamics
Hanlin Kong, Jianan Wei, Yuntian Chen +2
High-fidelity three-dimensional turbulent flow fields are essential for scientific and engineering analyses, yet obtaining them through direct numerical simulation or high-resoluti…
Foundation Neural-Network Quantum States for Molecular Potential Energy Surfaces in Second Quantization
Lizhong Fu, Jianan Wei, Wenguan Wang +1
Second-quantized neural-network quantum states have achieved accurate molecular energies, but extending them across molecular geometries requires a shared representation of the geo…
Generalizable Neural Downscaling of Earth System Model Wind Fields via Continuous Dynamics Modeling
Chenxi Yu, Jianan Wei, Hanlin Kong +3
Accurate high-resolution wind field simulations are critical for resolving fine-scale atmospheric dynamics, yet the simulation of wind fields in Earth System Models (ESMs) remains…
Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation
Haotian Xu, Yue Hu, Zhengqiu Zhu +3
Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations, and translate this inferenc…
Hyperbolic Hierarchical Clustering for Visual Representation Learning
Jianan Wei, Guikun Chen, Zhiyuan Weng +3
We investigate the token mixer in vision backbones by revisiting clustering, one of the most classic approaches in machine learning. An effective token mixer is a fundamental compo…
CoVStream: Edge-Cloud Collaboration for Understanding of Long Video Streams
Xu Liu, Guikun Chen, Zihao Yan +2
Long, continuous video streams are an increasingly critical driver of multimedia intelligence. Existing efforts often handle long videos with a sample-encode-reason approach using…
Uncertainty-Aware Gaussian Map for Vision-Language Navigation
Jianzhe Gao, Rui Liu, Yuxuan Xu +6
Vision-Language Navigation (VLN) requires an agent to navigate 3D environments following natural language instructions. During navigation, existing agents commonly encounter percep…
Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis
Jianzhe Gao, Churan Wang, Weiyi Zhang +5
Medical video diagnosis involves inferring clinical decisions from dynamic tissue responses throughout examination processes. Existing methods rely on an end-to-end learning paradi…
Moving Beyond Diffusion: Hierarchy-to-Hierarchy Autoregression for fMRI-to-Image Reconstruction
Xu Zhang, Ruijie Quan, Wenguan Wang +1
Reconstructing visual stimuli from fMRI signals is a central challenge bridging machine learning and neuroscience. Recent diffusion-based methods typically map fMRI activity to a s…
DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation
Mu Chen, Liulei Li, Wenguan Wang +1
Top-leading solutions for Video Scene Graph Generation (VSGG) typically adopt an offline pipeline. Though demonstrating promising performance, they remain unable to handle real-tim…
A Survey of World Models for Autonomous Driving
Tuo Feng, Wenguan Wang, Yi Yang
Recent breakthroughs in autonomous driving have been propelled by advances in robust world modeling, fundamentally transforming how vehicles interpret dynamic scenes and execute sa…
Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models
Liulei Li, Wenguan Wang, Yi Yang
Prevalent human-object interaction (HOI) detection approaches typically leverage large-scale visual-linguistic models to help recognize events involving humans and objects. Though…
Vision-Language Navigation with Energy-Based Policy
Rui Liu, Wenguan Wang, Yi Yang
Vision-language navigation (VLN) requires an agent to execute actions following human instructions. Existing VLN models are optimized through expert demonstrations by supervised be…
Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation
Minghan Chen, Guikun Chen, Wenguan Wang +1
DETR introduces a simplified one-stage framework for scene graph generation (SGG) but faces challenges of sparse supervision and false negative samples. The former occurs because e…
Navigation Instruction Generation with BEV Perception and Large Language Models
Sheng Fan, Rui Liu, Wenguan Wang +1
Navigation instruction generation, which requires embodied agents to describe the navigation routes, has been of great interest in robotics and human-computer interaction. Existing…
Controllable Navigation Instruction Generation with Chain of Thought Prompting
Xianghao Kong, Jinyu Chen, Wenguan Wang +4
Instruction generation is a vital and multidisciplinary research area with broad applications. Existing instruction generation models are limited to generating instructions in a si…
Mutual Learning for Acoustic Matching and Dereverberation via Visual Scene-driven Diffusion
Jian Ma, Wenguan Wang, Yi Yang +1
Visual acoustic matching (VAM) is pivotal for enhancing the immersive experience, and the task of dereverberation is effective in improving audio intelligibility. Existing methods…
Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data
Tuo Feng, Wenguan Wang, Ruijie Quan +1
Current 3D self-supervised learning methods of 3D scenes face a data desert issue, resulting from the time-consuming and expensive collecting process of 3D scene data. Conversely,…
General and Task-Oriented Video Segmentation
Mu Chen, Liulei Li, Wenguan Wang +2
We present GvSeg, a general video segmentation framework for addressing four different video segmentation tasks (i.e., instance, semantic, panoptic, and exemplar-guided) while main…
MS2SL: Multimodal Spoken Data-Driven Continuous Sign Language Production
Jian Ma, Wenguan Wang, Yi Yang +1
Sign language understanding has made significant strides; however, there is still no viable solution for generating sign sequences directly from entire spoken content, e.g., text o…
Visual Knowledge in the Big Model Era: Retrospect and Prospect
Wenguan Wang, Yi Yang, Yunhe Pan
Visual knowledge is a new form of knowledge representation that can encapsulate visual concepts and their relations in a succinct, comprehensive, and interpretable manner, with a d…
Clustering for Protein Representation Learning
Ruijie Quan, Wenguan Wang, Fan Ma +2
Protein representation learning is a challenging task that aims to capture the structure and function of proteins from their amino acid sequences. Previous methods largely ignored…
Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity
Ruijie Quan, Wenguan Wang, Zhibo Tian +2
Reconstructing the viewed images from human brain activity bridges human and computer vision through the Brain-Computer Interface. The inherent variability in brain function betwee…
Neural Clustering based Visual Representation Learning
Guikun Chen, Xia Li, Yi Yang +1
We investigate a fundamental aspect of machine vision: the measurement of features, by revisiting clustering, one of the most classic approaches in machine learning and data analys…