126 citations · 419 across the 27 of their papers we have counts for
28 papers
FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection
Haotian Zhang, Hao Chen, Han Guo +2
Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at each spatial location over…
TaCo: Capturing Spatio-Temporal Semantic Consistency in Remote Sensing Change Detection
Han Guo, Chenyang Liu, Haotian Zhang +3
Remote sensing change detection (RSCD) aims to identify surface changes across bi-temporal satellite images. Most previous methods rely solely on mask supervision, which effectivel…
FoBa: A Foreground-Background co-Guided Method and New Benchmark for Remote Sensing Semantic Change Detection
Haotian Zhang, Han Guo, Keyan Chen +3
Despite the remarkable progress achieved in remote sensing semantic change detection (SCD), two major challenges remain. At the data level, existing SCD datasets suffer from limite…
The Fourth Monocular Depth Estimation Challenge
Anton Obukhov, Matteo Poggi, Fabio Tosi +54
This paper presents the results of the fourth edition of the Monocular Depth Estimation Challenge (MDEC), which focuses on zero-shot generalization to the SYNS-Patches benchmark, a…
Efficient Semantic Splatting for Remote Sensing Multi-view Segmentation
Zipeng Qi, Hao Chen, Haotian Zhang +2
In this paper, we propose a novel semantic splatting approach based on Gaussian Splatting to achieve efficient and low-latency. Our method projects the RGB attributes and semantic…
A Late-Stage Bitemporal Feature Fusion Network for Semantic Change Detection
Chenyao Zhou, Haotian Zhang, Han Guo +2
Semantic change detection is an important task in geoscience and earth observation. By producing a semantic change map for each temporal phase, both the land use land cover categor…
CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection
Haotian Zhang, Keyan Chen, Chenyang Liu +3
Recently, the Mamba architecture based on state space models has demonstrated remarkable performance in a series of natural language processing tasks and has been rapidly applied t…
RSCaMa: Remote Sensing Image Change Captioning with State Space Model
Chenyang Liu, Keyan Chen, Bowen Chen +3
Remote Sensing Image Change Captioning (RSICC) aims to describe surface changes between multi-temporal remote sensing images in language, including the changed object categories, l…
MDepth: Self-supervised Two-Frame Multi-camera Metric Depth Estimation
Yingshuang Zou, Yikang Ding, Xi Qiu +2
This paper presents a novel self-supervised two-frame multi-camera metric depth estimation network, termed MDepth, which is designed to predict reliable scale-aware surroundi…
RSBuilding: Towards General Remote Sensing Image Building Extraction and Change Detection with Foundation Model
Mingze Wang, Lili Su, Cilin Yan +4
The intelligent interpretation of buildings plays a significant role in urban planning and management, macroeconomic analysis, population dynamics, etc. Remote sensing image buildi…
Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis
Chenyang Liu, Keyan Chen, Haotian Zhang +3
Monitoring changes in the Earth's surface is crucial for understanding natural processes and human impacts, necessitating precise and comprehensive interpretation methodologies. Re…
Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection
Keyan Chen, Chengyang Liu, Wenyuan Li +5
Change detection, a prominent research area in remote sensing, is pivotal in observing and analyzing surface transformations. Despite significant advancements achieved through deep…
Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change Captioning
Chenyang Liu, Keyan Chen, Zipeng Qi +3
The existing methods for Remote Sensing Image Change Captioning (RSICC) perform well in simple scenes but exhibit poorer performance in complex scenes. This limitation is primarily…
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model
Keyan Chen, Chenyang Liu, Hao Chen +4
Leveraging the extensive training data from SA-1B, the Segment Anything Model (SAM) demonstrates remarkable generalization and zero-shot capabilities. However, as a category-agnost…
Continuous Cross-resolution Remote Sensing Image Change Detection
Hao Chen, Haotian Zhang, Keyan Chen +4
Most contemporary supervised Remote Sensing (RS) image Change Detection (CD) approaches are customized for equal-resolution bitemporal images. Real-world applications raise the nee…
Sobolev Training for Implicit Neural Representations with Approximated Image Derivatives
Wentao Yuan, Qingtian Zhu, Xiangyue Liu +3
Recently, Implicit Neural Representations (INRs) parameterized by neural networks have emerged as a powerful and promising tool to represent different kinds of signals due to its c…
KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view Stereo
Yikang Ding, Qingtian Zhu, Xiangyue Liu +3
Supervised multi-view stereo (MVS) methods have achieved remarkable progress in terms of reconstruction quality, but suffer from the challenge of collecting large-scale ground-trut…
GLIPv2: Unifying Localization and Vision-Language Understanding
Haotian Zhang, Pengchuan Zhang, Xiaowei Hu +7
We present GLIPv2, a grounded VL understanding model, that serves both localization tasks (e.g., object detection, instance segmentation) and Vision-Language (VL) understanding tas…
Grounded Language-Image Pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang +9
This paper presents a grounded language-image pre-training (GLIP) model for learning object-level, language-aware, and semantic-rich visual representations. GLIP unifies object det…
TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers
Yikang Ding, Wentao Yuan, Qingtian Zhu +4
In this paper, we present TransMVSNet, based on our exploration of feature matching in multi-view stereo (MVS). We analogize MVS back to its nature of a feature matching task and t…
MegLoc: A Robust and Accurate Visual Localization Pipeline
Shuxue Peng, Zihang He, Haotian Zhang +4
In this paper, we present a visual localization pipeline, namely MegLoc, for robust and accurate 6-DoF pose estimation under varying scenarios, including indoor and outdoor scenes,…
Method Towards CVPR 2021 SimLocMatch Challenge
Xiaopeng Bi, Ran Yan, Zheng Chai +2
This report describes Megvii-3D team's approach towards SimLocMatch Challenge @ CVPR 2021 Image Matching Workshop.
Method Towards CVPR 2021 Image Matching Challenge
Xiaopeng Bi, Yu Chen, Xinyang Liu +5
This report describes Megvii-3D team's approach towards CVPR 2021 Image Matching Workshop.
ELSD: Efficient Line Segment Detector and Descriptor
Haotian Zhang, Yicheng Luo, Fangbo Qin +2
We present the novel Efficient Line Segment Detector and Descriptor (ELSD) to simultaneously detect line segments and extract their descriptors in an image. Unlike the traditional…