activity
20222026
most citedTowards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depth

6 citations · 20 across the 16 of their papers we have counts for

collaborators
Showing cs.CVShow all

15 papers · 1 filter

cs.CV2026

ChartSync: A Benchmark for Visuo-Logical Cascading Chart Editing

Jiakang Yu, Yixuan Chai, Tianci Wang +7

Generative image editing models struggle with structured statistical charts when data modifications require geometric synchronization. We formalize this task as Visuo-Logical Casca…

cs.CV2026

Unlocking the Power of Critical Factors for 3D Visual Geometry Estimation

Guangkai Xu, Hua Geng, Huanyi Zheng +4

Feed-forward visual geometry estimation has recently made rapid progress. However, an important gap remains: multi-frame models usually produce better cross-frame consistency, yet…

cs.CV2026

CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models

Junming Huang, Chi Wang, Letian Li +5

Large Language Models(LLMs) have revolutionized text generation and multimodal perception,but their capabilities in 3D content generation remain underexplored. Existing methods com…

cs.CV2025★ 1 cited

Generative Video Matting

Yongtao Ge, Kangyang Xie, Guangkai Xu +6

Video matting has traditionally been limited by the lack of high-quality ground-truth data. Most existing video matting datasets provide only human-annotated imperfect alpha and fo…

cs.CV2024

Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation

Muzhi Zhu, Yang Liu, Zekai Luo +5

The Diffusion Model has not only garnered noteworthy achievements in the realm of image generation but has also demonstrated its potential as an effective pretraining method utiliz…

cs.CV2024

GeoBench: Benchmarking and Analyzing Monocular Geometry Estimation Models

Yongtao Ge, Guangkai Xu, Zhiyue Zhao +5

Recent advances in discriminative and generative pretraining have yielded geometry estimation models with strong generalization capabilities. While discriminative monocular geometr…

cs.CV2024

DiffCalib: Reformulating Monocular Camera Calibration as Diffusion-Based Dense Incident Map Generation

Xiankang He, Guangkai Xu, Bo Zhang +3

Monocular camera calibration is a key precondition for numerous 3D vision applications. Despite considerable advancements, existing methods often hinge on specific assumptions and…

cs.CV2024★ 2 cited

What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Guangkai Xu, Yongtao Ge, Mingyu Liu +5

Extensive pre-training with large data is indispensable for downstream geometry and semantic visual perception tasks. Thanks to large-scale text-to-image (T2I) pretraining, recent…

cs.CV2023★ 1 cited

Improving Neural Indoor Surface Reconstruction with Mask-Guided Adaptive Consistency Constraints

Xinyi Yu, Liqin Lu, Jintao Rong +2

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implici…

cs.CV2023★ 1 cited

FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models

Guangkai Xu, Wei Yin, Hao Chen +3

3D scene reconstruction is a long-standing vision task. Existing approaches can be categorized into geometry-based and learning-based methods. The former leverages multi-view geome…

cs.CV2023

The Second Monocular Depth Estimation Challenge

Jaime Spencer, C. Stella Qian, Michaela Trescakova +40

This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…

cs.CV2022★ 3 cited

DETRDistill: A Universal Knowledge Distillation Framework for DETR-families

Jiahao Chang, Shuo Wang, Haiming Xu +3

Transformer-based detectors (DETRs) are becoming popular for their simple framework, but the large model size and heavy time consumption hinder their deployment in the real world.…

cs.CV2022★ 4 cited

Towards Domain-agnostic Depth Completion

Guangkai Xu, Wei Yin, Jianming Zhang +4

Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task domains. We present a method to complete sparse/semi-dense, n…

cs.CV2022★ 2 cited

Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation

Kai Cheng, Hao Chen, Wei Yin +2

Multi-view depth estimation plays a critical role in reconstructing and understanding the 3D world. Recent learning-based methods have made significant progress in it. However, mul…

cs.CV2022★ 6 cited

Towards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depth

Guangkai Xu, Wei Yin, Hao Chen +4

Existing monocular depth estimation methods have achieved excellent robustness in diverse scenes, but they can only retrieve affine-invariant depth, up to an unknown scale and shif…