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Dexterous Robotic Piano Playing at Scale
Le Chen, Yi Zhao, Jan Schneider +7
Endowing robot hands with human-level dexterity has been a long-standing goal in robotics. Bimanual robotic piano playing represents a particularly challenging task: it is high-dim…
3D Gaussian Splatting with Fisheye Images: Field of View Analysis and Depth-Based Initialization
Ulas Gunes, Matias Turkulainen, Mikhail Silaev +2
We present the first evaluation of 3D Gaussian Splatting methods on real fisheye imagery with fields of view above 180\textdegree{}. Our study evaluates Fisheye-GS \cite{liao2024fi…
Smoothing Slot Attention Iterations and Recurrences
Rongzhen Zhao, Wenyan Yang, Juho Kannala +1
Slot Attention (SA) lies at the heart of mainstream Object-Centric Learning (OCL). Image features can be aggregated into object-level representations by SA \textit{iteratively} ref…
Predicting Video Slot Attention Queries from Random Slot-Feature Pairs
Rongzhen Zhao, Jian Li, Juho Kannala +1
Unsupervised video Object-Centric Learning (OCL) is promising as it enables object-level scene representation and understanding as we humans do. Mainstream video OCL methods adopt…
Slot Attention with Re-Initialization and Self-Distillation
Rongzhen Zhao, Yi Zhao, Juho Kannala +1
Unlike popular solutions based on dense feature maps, Object-Centric Learning (OCL) represents visual scenes as sub-symbolic object-level feature vectors, termed slots, which are h…
FingerVeinSyn-5M: A Million-Scale Dataset and Benchmark for Finger Vein Recognition
Yinfan Wang, Jie Gui, Baosheng Yu +4
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the ad…
FIORD: A Fisheye Indoor-Outdoor Dataset with LIDAR Ground Truth for 3D Scene Reconstruction and Benchmarking
Ulas Gunes, Matias Turkulainen, Xuqian Ren +3
The development of large-scale 3D scene reconstruction and novel view synthesis methods mostly rely on datasets comprising perspective images with narrow fields of view (FoV). Whil…
A Dataset for Semantic Segmentation in the Presence of Unknowns
Zakaria Laskar, Tomas Vojir, Matej Grcic +6
Before deployment in the real-world deep neural networks require thorough evaluation of how they handle both knowns, inputs represented in the training data, and unknowns (anomalie…
A2-GNN: Angle-Annular GNN for Visual Descriptor-free Camera Relocalization
Yejun Zhang, Shuzhe Wang, Juho Kannala
Visual localization involves estimating the 6-degree-of-freedom (6-DoF) camera pose within a known scene. A critical step in this process is identifying pixel-to-point corresponden…
Vector-Quantized Vision Foundation Models for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) aggregates image or video feature maps into object-level feature vectors, termed \textit{slots}. It's self-supervision of reconstructing the input fro…
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…
Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models
Hao Dong, Moru Liu, Kaiyang Zhou +4
In real-world scenarios, achieving domain adaptation and generalization poses significant challenges, as models must adapt to or generalize across unknown target distributions. Ext…