Search Results for author: Yunlu Chen

Found 9 papers, 5 papers with code

Graph Neural Networks for Learning Equivariant Representations of Neural Networks

1 code implementation18 Mar 2024 Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang

Neural networks that process the parameters of other neural networks find applications in domains as diverse as classifying implicit neural representations, generating neural network weights, and predicting generalization errors.

Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation

1 code implementation29 Jan 2024 Jie Liu, Wenzhe Yin, Haochen Wang, Yunlu Chen, Jan-Jakob Sonke, Efstratios Gavves

Existing prototype-based methods rely on support prototypes to guide the segmentation of query point clouds, but they encounter challenges when significant object variations exist between the support prototypes and query features.

Point Cloud Segmentation Transfer Learning

Motion Flow Matching for Human Motion Synthesis and Editing

no code implementations14 Dec 2023 Vincent Tao Hu, Wenzhe Yin, Pingchuan Ma, Yunlu Chen, Basura Fernando, Yuki M Asano, Efstratios Gavves, Pascal Mettes, Bjorn Ommer, Cees G. M. Snoek

In this paper, we propose \emph{Motion Flow Matching}, a novel generative model designed for human motion generation featuring efficient sampling and effectiveness in motion editing applications.

Motion Interpolation motion prediction +1

Guided Diffusion from Self-Supervised Diffusion Features

no code implementations14 Dec 2023 Vincent Tao Hu, Yunlu Chen, Mathilde Caron, Yuki M. Asano, Cees G. M. Snoek, Bjorn Ommer

However, recent studies have revealed that the feature representation derived from diffusion model itself is discriminative for numerous downstream tasks as well, which prompts us to propose a framework to extract guidance from, and specifically for, diffusion models.

Self-Supervised Learning

Kernel Learning in Ridge Regression "Automatically" Yields Exact Low Rank Solution

1 code implementation18 Oct 2023 Yunlu Chen, Yang Li, Keli Liu, Feng Ruan

Assuming that the covariates have nonzero explanatory power for the response only through a low dimensional subspace (central mean subspace), we find that the global minimizer of the finite sample kernel learning objective is also low rank with high probability.

regression

3D Equivariant Graph Implicit Functions

no code implementations31 Mar 2022 Yunlu Chen, Basura Fernando, Hakan Bilen, Matthias Nießner, Efstratios Gavves

In this work, we address two key limitations of such representations, in failing to capture local 3D geometric fine details, and to learn from and generalize to shapes with unseen 3D transformations.

Unsharp Mask Guided Filtering

1 code implementation2 Jun 2021 Zenglin Shi, Yunlu Chen, Efstratios Gavves, Pascal Mettes, Cees G. M. Snoek

The state-of-the-art leverages deep networks to estimate the two core coefficients of the guided filter.

Denoising

3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation

no code implementations3 Oct 2019 Yunlu Chen, Thomas Mensink, Efstratios Gavves

We propose to model the effective receptive field of 2D convolution based on the scale and locality from the 3D neighborhood.

Segmentation Semantic Segmentation

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