6 citations · 20 across the 16 of their papers we have counts for
16 papers
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…
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…
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…
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…
POMATO: Marrying Pointmap Matching with Temporal Motion for Dynamic 3D Reconstruction
Songyan Zhang, Yongtao Ge, Jinyuan Tian +4
3D reconstruction in dynamic scenes primarily relies on the combination of geometry estimation and matching modules where the latter task is pivotal for distinguishing dynamic regi…
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…
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…
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…
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…
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…
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…
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…
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.…
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…
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…
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…