Search Results for author: Gregory Rogez

Found 20 papers, 5 papers with code

T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences

no code implementations2 Jun 2024 Taeryung Lee, Fabien Baradel, Thomas Lucas, Kyoung Mu Lee, Gregory Rogez

To address these issues, we introduce simple yet effective T2LM, a continuous long-term generation framework that can be trained without sequential data.

Action Generation Decoder +1

Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

1 code implementation26 Feb 2024 Pau de Jorge, Riccardo Volpi, Puneet K. Dokania, Philip H. S. Torr, Gregory Rogez

For example, we utilize it to augment Cityscapes samples by incorporating a subset of Pascal classes and demonstrate that models trained on such data achieve comparable performance to the Pascal-trained baseline.

Anomaly Segmentation Segmentation +1

SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstruction

no code implementations19 Sep 2023 Anilkumar Swamy, Vincent Leroy, Philippe Weinzaepfel, Fabien Baradel, Salma Galaaoui, Romain Bregier, Matthieu Armando, Jean-Sebastien Franco, Gregory Rogez

Recent hand-object interaction datasets show limited real object variability and rely on fitting the MANO parametric model to obtain groundtruth hand shapes.

3D Reconstruction Benchmarking +1

Reliability in Semantic Segmentation: Are We on the Right Track?

1 code implementation CVPR 2023 Pau de Jorge, Riccardo Volpi, Philip Torr, Gregory Rogez

We analyze a broad variety of models, spanning from older ResNet-based architectures to novel transformers and assess their reliability based on four metrics: robustness, calibration, misclassification detection and out-of-distribution (OOD) detection.

Out of Distribution (OOD) Detection Semantic Segmentation

MonoNHR: Monocular Neural Human Renderer

1 code implementation2 Oct 2022 Hongsuk Choi, Gyeongsik Moon, Matthieu Armando, Vincent Leroy, Kyoung Mu Lee, Gregory Rogez

Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas.

3D geometry

Barely-Supervised Learning: Semi-Supervised Learning with very few labeled images

no code implementations22 Dec 2021 Thomas Lucas, Philippe Weinzaepfel, Gregory Rogez

We propose a method to leverage self-supervised methods that provides training signal in the absence of confident pseudo-labels.

Pseudo Label

Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps

1 code implementation17 Dec 2020 Jens Lundell, Enric Corona, Tran Nguyen Le, Francesco Verdoja, Philippe Weinzaepfel, Gregory Rogez, Francesc Moreno-Noguer, Ville Kyrki

While there exists many methods for manipulating rigid objects with parallel-jaw grippers, grasping with multi-finger robotic hands remains a quite unexplored research topic.

Progressive Skeletonization: Trimming more fat from a network at initialization

1 code implementation ICLR 2021 Pau de Jorge, Amartya Sanyal, Harkirat S. Behl, Philip H. S. Torr, Gregory Rogez, Puneet K. Dokania

Recent studies have shown that skeletonization (pruning parameters) of networks \textit{at initialization} provides all the practical benefits of sparsity both at inference and training time, while only marginally degrading their performance.

The Open World of Micro-Videos

no code implementations31 Mar 2016 Phuc Xuan Nguyen, Gregory Rogez, Charless Fowlkes, Deva Ramanan

Micro-videos are six-second videos popular on social media networks with several unique properties.

Diversity TAG +1

Understanding Everyday Hands in Action From RGB-D Images

no code implementations ICCV 2015 Gregory Rogez, James S. Supancic III, Deva Ramanan

We analyze functional manipulations of handheld objects, formalizing the problem as one of fine-grained grasp classification.

Diversity

First-Person Pose Recognition Using Egocentric Workspaces

no code implementations CVPR 2015 Gregory Rogez, James S. Supancic III, Deva Ramanan

In egocentric views, hands and arms are observable within a well defined volume in front of the camera.

Pose Estimation

Egocentric Pose Recognition in Four Lines of Code

no code implementations29 Nov 2014 Gregory Rogez, James S. Supancic III, Deva Ramanan

We tackle the problem of estimating the 3D pose of an individual's upper limbs (arms+hands) from a chest mounted depth-camera.

Pose Estimation

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