activity
20172026
most citedFast Graph Representation Learning with PyTorch Geometric

1.3k citations · 1.5k across the 47 of their papers we have counts for

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Showing 2025Show all

11 papers · 1 filter

cs.CV2025

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

Zhipeng Du, Duolikun Danier, Jan Eric Lenssen +1

In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform because they rely on posed RGB-D…

cs.CV2025

MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation

Yannan He, Garvita Tiwari, Xiaohan Zhang +4

We introduce MoLingo, a text-to-motion (T2M) model that generates realistic, lifelike human motion by denoising in a continuous latent space. Recent works perform latent space diff…

cs.CV2025

AnyUp: Universal Feature Upsampling

Thomas Wimmer, Prune Truong, Marie-Julie Rakotosaona +4

We introduce AnyUp, a method for feature upsampling that can be applied to any vision feature at any resolution, without encoder-specific training. Existing learning-based upsample…

cs.CV2025

RefAM: Attention Magnets for Zero-Shot Referral Segmentation

Anna Kukleva, Enis Simsar, Alessio Tonioni +4

Most existing approaches to referring segmentation achieve strong performance only through fine-tuning or by composing multiple pre-trained models, often at the cost of additional…

cs.LG2025★ 8 cited

PyG 2.0: Scalable Learning on Real World Graphs

Matthias Fey, Jinu Sunil, Akihiro Nitta +10

PyG (PyTorch Geometric) has evolved significantly since its initial release, establishing itself as a leading framework for Graph Neural Networks. In this paper, we present Pyg 2.0…

cs.LG2025

Spatial Reasoners for Continuous Variables in Any Domain

Bart Pogodzinski, Christopher Wewer, Bernt Schiele +1

We present Spatial Reasoners, a software framework to perform spatial reasoning over continuous variables with generative denoising models. Denoising generative models have become…