activity
20192026
most citedGS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

11 citations · 36 across the 32 of their papers we have counts for

collaborators
Showing cs.CVShow all

20 papers · 1 filter

cs.CV2026

Q-GeoMem: Question-Guided Geometric Memory for Video Spatial Reasoning

Xianqiang Gao, Qizhi Chen, Delin Qu +5

Video spatial reasoning requires accumulating viewpoint-dependent evidence over time while retaining information useful to the question being asked. Existing spatial video-language…

cs.CV2026

Understanding Degradation with Vision Language Model

Guanzhou Lan, Chenyi Liao, Yuqi Yang +5

Understanding visual degradations is a critical yet challenging problem in computer vision. While recent Vision-Language Models (VLMs) excel at qualitative description, they often…

cs.CV2025

Cross from Left to Right Brain: Adaptive Text Dreamer for Vision-and-Language Navigation

Pingrui Zhang, Yifei Su, Pengyuan Wu +7

Vision-and-Language Navigation (VLN) requires the agent to navigate by following natural instructions under partial observability, making it difficult to align perception with lang…

cs.CV2025

AerialVG: A Challenging Benchmark for Aerial Visual Grounding by Exploring Positional Relations

Junli Liu, Qizhi Chen, Zhigang Wang +6

Visual grounding (VG) aims to localize target objects in an image based on natural language descriptions. In this paper, we propose AerialVG, a new task focusing on visual groundin…

cs.CV2025

Openfly: A comprehensive platform for aerial vision-language navigation

Yunpeng Gao, Chenhui Li, Zhongrui You +20

Vision-Language Navigation (VLN) aims to guide agents by leveraging language instructions and visual cues, playing a pivotal role in embodied AI. Indoor VLN has been extensively st…

cs.CV2025

Exploring the Potential of Encoder-free Architectures in 3D LMMs

Yiwen Tang, Zoey Guo, Zhuhao Wang +8

Encoder-free architectures have been preliminarily explored in the 2D Large Multimodal Models (LMMs), yet it remains an open question whether they can be effectively applied to 3D…

cs.CV2024

Night-to-Day Translation via Illumination Degradation Disentanglement

Guanzhou Lan, Yuqi Yang, Zhigang Wang +3

Night-to-Day translation (Night2Day) aims to achieve day-like vision for nighttime scenes. However, processing night images with complex degradations remains a significant challeng…

cs.CV2024

Open-Vocabulary Octree-Graph for 3D Scene Understanding

Zhigang Wang, Yifei Su, Chenhui Li +4

Open-vocabulary 3D scene understanding is indispensable for embodied agents. Recent works leverage pretrained vision-language models (VLMs) for object segmentation and project them…

cs.CV2024

Efficient Diffusion as Low Light Enhancer

Guanzhou Lan, Qianli Ma, Yuqi Yang +4

The computational burden of the iterative sampling process remains a major challenge in diffusion-based Low-Light Image Enhancement (LLIE). Current acceleration methods, whether tr…

cs.CV2024★ 6 cited

Learning 2D Invariant Affordance Knowledge for 3D Affordance Grounding

Xianqiang Gao, Pingrui Zhang, Delin Qu +4

3D Object Affordance Grounding aims to predict the functional regions on a 3D object and has laid the foundation for a wide range of applications in robotics. Recent advances tackl…

cs.CV2024★ 1 cited

SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation

Junjie Zhang, Chenjia Bai, Haoran He +5

Acquiring a multi-task imitation policy in 3D manipulation poses challenges in terms of scene understanding and action prediction. Current methods employ both 3D representation and…

cs.CV2024

Any2Point: Empowering Any-modality Large Models for Efficient 3D Understanding

Yiwen Tang, Ray Zhang, Jiaming Liu +8

Large foundation models have recently emerged as a prominent focus of interest, attaining superior performance in widespread scenarios. Due to the scarcity of 3D data, many efforts…

cs.CV2024

HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation

Linglin Jing, Yiming Ding, Yunpeng Gao +7

Event-based semantic segmentation has gained popularity due to its capability to deal with scenarios under high-speed motion and extreme lighting conditions, which cannot be addres…

cs.CV2023

X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-modal Knowledge Transfer

Linglin Jing, Ying Xue, Xu Yan +7

The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the spars…

cs.CV2023★ 11 cited

GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

Chi Yan, Delin Qu, Dan Xu +4

In this paper, we introduce \textbf{GS-SLAM} that first utilizes 3D Gaussian representation in the Simultaneous Localization and Mapping (SLAM) system. It facilitates a better bala…

cs.CV2023★ 3 cited

One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field

Weichuang Li, Longhao Zhang, Dong Wang +7

Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image. Most pioneering methods rely…

cs.CV2023

Propagate And Calibrate: Real-time Passive Non-line-of-sight Tracking

Yihao Wang, Zhigang Wang, Bin Zhao +3

Non-line-of-sight (NLOS) tracking has drawn increasing attention in recent years, due to its ability to detect object motion out of sight. Most previous works on NLOS tracking rely…

cs.CV2023★ 1 cited

Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction

Delin Qu, Yizhen Lao, Zhigang Wang +3

This paper addresses the problem of rolling shutter correction in complex nonlinear and dynamic scenes with extreme occlusion. Existing methods suffer from two main drawbacks. Firs…

cs.CV2023★ 2 cited

ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidance

Zoey Guo, Yiwen Tang, Ray Zhang +4

Understanding 3D scenes from multi-view inputs has been proven to alleviate the view discrepancy issue in 3D visual grounding. However, existing methods normally neglect the view c…

cs.CV2019★ 2 cited

A CNN-RNN Architecture for Multi-Label Weather Recognition

Bin Zhao, Xuelong Li, Xiaoqiang Lu +1

Weather Recognition plays an important role in our daily lives and many computer vision applications. However, recognizing the weather conditions from a single image remains challe…