1 citations · 1 across the 10 of their papers we have counts for
11 papers
SplatGuide: Geometric Priors from 3D Gaussians for Pose-Free Novel View Synthesis
Yejun Zhang, Zihan Wang, Xu Ji +8
Generating photorealistic novel views from unposed images requires both 3D geometric understanding and the ability to synthesize unseen content. A natural strategy combines feed-fo…
Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
Riccardo Mereu, Aidan Scannell, Yuxin Hou +6
World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model C…
Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data
Yi Zhao, Aidan Scannell, Wenshuai Zhao +7
Leveraging offline data is a promising way to improve the sample efficiency of online reinforcement learning (RL). This paper expands the pool of usable data for offline-to-online…
Expansion of Visual Hints for Improved Generalization in Stereo Matching
Andrea Pilzer, Yuxin Hou, Niki Loppi +2
We introduce visual hints expansion for guiding stereo matching to improve generalization. Our work is motivated by the robustness of Visual Inertial Odometry (VIO) in computer vis…
Novel View Synthesis via Depth-guided Skip Connections
Yuxin Hou, Arno Solin, Juho Kannala
We introduce a principled approach for synthesizing new views of a scene given a single source image. Previous methods for novel view synthesis can be divided into image-based rend…
Movement-induced Priors for Deep Stereo
Yuxin Hou, Muhammad Kamran Janjua, Juho Kannala +1
We propose a method for fusing stereo disparity estimation with movement-induced prior information. Instead of independent inference frame-by-frame, we formulate the problem as a n…
Deep Automodulators
Ari Heljakka, Yuxin Hou, Juho Kannala +1
We introduce a new category of generative autoencoders called automodulators. These networks can faithfully reproduce individual real-world input images like regular autoencoders,…
Gaussian Process Priors for View-Aware Inference
Yuxin Hou, Ari Heljakka, Arno Solin
While frame-independent predictions with deep neural networks have become the prominent solutions to many computer vision tasks, the potential benefits of utilizing correlations be…
Iterative Path Reconstruction for Large-Scale Inertial Navigation on Smartphones
Santiago Cortés Reina, Yuxin Hou, Juho Kannala +1
Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliab…
Multi-View Stereo by Temporal Nonparametric Fusion
Yuxin Hou, Juho Kannala, Arno Solin
We propose a novel idea for depth estimation from multi-view image-pose pairs, where the model has capability to leverage information from previous latent-space encodings of the sc…
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation
Yuxin Hou, Arno Solin, Juho Kannala
This paper presents a novel method, MaskMVS, to solve depth estimation for unstructured multi-view image-pose pairs. In the plane-sweep procedure, the depth planes are sampled by h…