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Jean-Michel Morel

8 accepted papers

2026

LAMIGAUSS: PITCHING RADIATIVE GAUSSIAN FOR SPARSE-VIEW X-RAY LAMINOGRAPHY RECONSTRUCTION

ICASSP 2026poster

X-ray Computed Laminography (CL) is essential for non-destructive inspection of plate-like structures in applications such as microchips and composite battery materials, where traditional computed tomography (CT) struggles due to geometric constraints. However, reconstructing high-quality volumes fr…

Cited by 0SourcePDFScholar
2026

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation

ICLR 2026poster

The rapid advancement of video diffusion models has been hindered by fundamental limitations in temporal modeling, particularly the rigid synchronization of frame evolution imposed by conventional scalar timestep variables. While task-specific adaptations and autoregressive models have sought to add…

Cited by 0SourcecodeScholar
2025

Detection and Geographic Localization of Natural Objects in the Wild: A Case Study on Palms

IJCAI 2025

Palms are ecologically and economically indicators of tropical forest health, biodiversity, and human impact that support local economies and global forest product supply chains. While palm detection in plantations is well-studied, efforts to map naturally occurring palms in dense forests remain lim

2025

Optimal and Efficient Binary Questioning for Accelerated Annotation

AAAI 2025technical

Even though data annotation is extremely important for interpretability, research, and development of artificial intelligence solutions, annotating data remains costly. Research efforts such as active learning or few-shot learning alleviate the cost by increasing sample efficiency, yet the problem o…

Cited by 0SourcePDFScholar
2025

SGSST: Scaling Gaussian Splatting Style Transfer

CVPR 2025poster

Applying style transfer to a full 3D environment is a challenging task that has seen many developments since the advent of neural rendering. 3D Gaussian splatting (3DGS) has recently pushed further many limits of neural rendering in terms of training speed and reconstruction quality. This work intro…

2020

An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image Forensics

CVPR 2020poster

Automatically finding suspicious regions in a potentially forged image by splicing, inpainting or copy-move remains a widely open problem. Blind detection neural networks trained on benchmark data are flourishing. Yet, these methods do not provide an explanation of their detections. The more traditi…

Cited by 60PDFcodeScholar
2019

Model-Blind Video Denoising via Frame-To-Frame Training

CVPR 2019poster

Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available. This makes model based video processing a still more complex task. In this paper we propose a fully blind video denoising method, with two versions off-line and on…

Cited by 104PDFcodeScholar