8 citations · 17 across the 16 of their papers we have counts for
19 papers
Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model
Liming Lu, Xianzheng Ma, Wenkun He +14
Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical principles. Existing approac…
AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels
Javier Tirado-Garín, Alan Savio Paul, Shuai Chen +5
Neural map matchers estimate an image's 3-DoF pose relative to a 2D map. These models are trained on large-scale datasets of geo-referenced images, whose position and heading label…
NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics
Qizhen Ying, Guangming Wang, Yangchen Pan +3
Physics-grounded video generation requires controllable 3D object dynamics that remain physically consistent under contact, deformation, and external forcing. Existing trajectory-b…
Temporal Difference Learning for Diffusion Models
Qizhen Ying, Yangchen Pan, Victor Adrian Prisacariu +1
Diffusion models are typically trained with objectives that focus on local denoising targets at individual time steps (or adjacent pairs), which do not enforce consistency between…
Do 3D Large Language Models Really Understand 3D Spatial Relationships?
Xianzheng Ma, Tao Sun, Shuai Chen +7
Recent 3D Large-Language Models (3D-LLMs) claim to understand 3D worlds, especially spatial relationships among objects. Yet, we find that simply fine-tuning a language model on te…
Scene Coordinate Reconstruction Priors
Wenjing Bian, Axel Barroso-Laguna, Tommaso Cavallari +2
Scene coordinate regression (SCR) models have proven to be powerful implicit scene representations for 3D vision, enabling visual relocalization and structure-from-motion. SCR mode…
ACE-G: Improving Generalization of Scene Coordinate Regression Through Query Pre-Training
Leonard Bruns, Axel Barroso-Laguna, Tommaso Cavallari +4
Scene coordinate regression (SCR) has established itself as a promising learning-based approach to visual relocalization. After mere minutes of scene-specific training, SCR models…
A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features
Axel Barroso-Laguna, Tommaso Cavallari, Victor Adrian Prisacariu +1
Visually localizing an image, i.e., estimating its camera pose, requires building a scene representation that serves as a visual map. The representation we choose has direct conseq…
Reflect3r: Single-View 3D Stereo Reconstruction Aided by Mirror Reflections
Jing Wu, Zirui Wang, Iro Laina +1
Mirror reflections are common in everyday environments and can provide stereo information within a single capture, as the real and reflected virtual views are visible simultaneousl…
Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset
Zirui Wang, Wenjing Bian, Xinghui Li +4
We introduce Oxford Day-and-Night, a large-scale, egocentric dataset for novel view synthesis (NVS) and visual relocalisation under challenging lighting conditions. Existing datase…
Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs
Brandon Smart, Chuanxia Zheng, Iro Laina +1
In this paper, we introduce Splatt3R, a pose-free, feed-forward method for in-the-wild 3D reconstruction and novel view synthesis from stereo pairs. Given uncalibrated natural imag…
GS-CPR: Efficient Camera Pose Refinement via 3D Gaussian Splatting
Changkun Liu, Shuai Chen, Yash Bhalgat +5
We leverage 3D Gaussian Splatting (3DGS) as a scene representation and propose a novel test-time camera pose refinement (CPR) framework, GS-CPR. This framework enhances the localiz…
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Xianzheng Ma, Brandon Smart, Yash Bhalgat +14
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interact…
Map-Relative Pose Regression for Visual Re-Localization
Shuai Chen, Tommaso Cavallari, Victor Adrian Prisacariu +1
Pose regression networks predict the camera pose of a query image relative to a known environment. Within this family of methods, absolute pose regression (APR) has recently shown…
CrossScore: Towards Multi-View Image Evaluation and Scoring
Zirui Wang, Wenjing Bian, Victor Adrian Prisacariu
We introduce a novel cross-reference image quality assessment method that effectively fills the gap in the image assessment landscape, complementing the array of established evalua…
Scene Coordinate Reconstruction: Posing of Image Collections via Incremental Learning of a Relocalizer
Eric Brachmann, Jamie Wynn, Shuai Chen +4
We address the task of estimating camera parameters from a set of images depicting a scene. Popular feature-based structure-from-motion (SfM) tools solve this task by incremental r…
GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing
Jing Wu, Jia-Wang Bian, Xinghui Li +4
We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS a…
HR-APR: APR-agnostic Framework with Uncertainty Estimation and Hierarchical Refinement for Camera Relocalisation
Changkun Liu, Shuai Chen, Yukun Zhao +3
Absolute Pose Regressors (APRs) directly estimate camera poses from monocular images, but their accuracy is unstable for different queries. Uncertainty-aware APRs provide uncertain…
SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching
Xinghui Li, Jingyi Lu, Kai Han +1
In this paper, we address the challenge of matching semantically similar keypoints across image pairs. Existing research indicates that the intermediate output of the UNet within t…