7 citations · 28 across the 26 of their papers we have counts for
22 papers · 1 filter
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…
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…
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…
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…
Clustering Propagation for Universal Medical Image Segmentation
Yuhang Ding, Liulei Li, Wenguan Wang +1
Prominent solutions for medical image segmentation are typically tailored for automatic or interactive setups, posing challenges in facilitating progress achieved in one task to an…
LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels
Tuo Feng, Wenguan Wang, Fan Ma +1
Autonomous systems need to process large-scale, sparse, and irregular point clouds with limited compute resources. Consequently, it is essential to develop LiDAR perception methods…
Volumetric Environment Representation for Vision-Language Navigation
Rui Liu, Wenguan Wang, Yi Yang
Vision-language navigation (VLN) requires an agent to navigate through an 3D environment based on visual observations and natural language instructions. It is clear that the pivota…
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li +2
Recent LLM-driven visual agents mainly focus on solving image-based tasks, which limits their ability to understand dynamic scenes, making it far from real-life applications like g…
A Survey on 3D Gaussian Splatting
Guikun Chen, Wenguan Wang
3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for…
Neural-Logic Human-Object Interaction Detection
Liulei Li, Jianan Wei, Wenguan Wang +1
The interaction decoder utilized in prevalent Transformer-based HOI detectors typically accepts pre-composed human-object pairs as inputs. Though achieving remarkable performance,…