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Alexandre Morgand

@Almorgand • 2,136 subscribers

Computer Vision Research Scientist at @simulon, music lover , fond of scientific/musical/geeky/useless stuff. I'm posting papers on whatever I found amazing :)

Shorts

"Content-Aware Texturing for Gaussian Splatting" TL;DR: Texturing instead of millions of Gaussians for fine details; fixed texel size

"Content-Aware Texturing for Gaussian Splatting" TL;DR: Texturing instead of millions of Gaussians for fine details; fixed texel size

34,511 Aufrufe

Videos

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"MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer" TL;DR: learns a continuous mesh latent space and generates vertices and connectivity in parallel with flow matching, producing quality 3D meshes up to 18× faster than autoregressive.

"MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer" TL;DR: learns a continuous mesh latent space and generates vertices and connectivity in parallel with flow matching, producing quality 3D meshes up to 18× faster than autoregressive.

Alexandre Morgand

43,016 Aufrufe • vor 1 Monat

"ROSE: Remove Objects with Side Effects in Videos" TL;DR: Diffusion transformer; five common cases: shadows, reflections, light, translucency and mirror as video side effects to remove

"ROSE: Remove Objects with Side Effects in Videos" TL;DR: Diffusion transformer; five common cases: shadows, reflections, light, translucency and mirror as video side effects to remove

Alexandre Morgand

85,858 Aufrufe • vor 10 Monaten

"Fast 4D Mesh Generation by Spatio-Temporal Attention Chains" TL;DR: training-free spatio-temporal attention chains generate topology-consistent 4D meshes from video 13× faster while improving temporal correspondence quality

"Fast 4D Mesh Generation by Spatio-Temporal Attention Chains" TL;DR: training-free spatio-temporal attention chains generate topology-consistent 4D meshes from video 13× faster while improving temporal correspondence quality

Alexandre Morgand

13,728 Aufrufe • vor 1 Monat

"Triangle Splatting SLAM" TL;DR: the first dense RGB-D SLAM system built on differentiable triangle splatting, enabling real-time tracking, mesh reconstruction, collision checking, and scene editing from a unified representation.

"Triangle Splatting SLAM" TL;DR: the first dense RGB-D SLAM system built on differentiable triangle splatting, enabling real-time tracking, mesh reconstruction, collision checking, and scene editing from a unified representation.

Alexandre Morgand

11,900 Aufrufe • vor 1 Monat

DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding TL;DR: DINO-X Pro: sota model with enhanced perception capabilities for various scenarios; DINO-X Edge: model optimized for faster inference speed and better suited for deployment on edge devices

DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding TL;DR: DINO-X Pro: sota model with enhanced perception capabilities for various scenarios; DINO-X Edge: model optimized for faster inference speed and better suited for deployment on edge devices

Alexandre Morgand

60,726 Aufrufe • vor 1 Jahr

"YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting" TL;DR: a unified 3D Gaussian splatting model that reconstructs high-quality scene geometry and camera poses from unposed/uncalibrated images in a single forward pass.

"YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting" TL;DR: a unified 3D Gaussian splatting model that reconstructs high-quality scene geometry and camera poses from unposed/uncalibrated images in a single forward pass.

Alexandre Morgand

15,035 Aufrufe • vor 4 Monaten

"DVD: Dynamic Video Depth" TL;DR: Recovers temporally consistent depth from monocular videos using diffusion priors + geometric constraints, handling dynamic scenes and motion robustly.

"DVD: Dynamic Video Depth" TL;DR: Recovers temporally consistent depth from monocular videos using diffusion priors + geometric constraints, handling dynamic scenes and motion robustly.

Alexandre Morgand

11,823 Aufrufe • vor 4 Monaten

Amodal3R: Amodal 3D Reconstruction from Occluded 2D Images TL;DR: Given partially visible objects within images, Amodal3R reconstructs semantically meaningful 3D assets with reasonable geometry and plausible appearance.

Amodal3R: Amodal 3D Reconstruction from Occluded 2D Images TL;DR: Given partially visible objects within images, Amodal3R reconstructs semantically meaningful 3D assets with reasonable geometry and plausible appearance.

Alexandre Morgand

23,300 Aufrufe • vor 1 Jahr

"Cameras as Relative Positional Encoding" TLDR: comparison for conditioning transformers on cameras: token-level raymap, attention-level relative pose encodings, a (new) relative encoding Projective Positional Encoding -> camera frustums, (int|ext)insics for relative pos encoding

"Cameras as Relative Positional Encoding" TLDR: comparison for conditioning transformers on cameras: token-level raymap, attention-level relative pose encodings, a (new) relative encoding Projective Positional Encoding -> camera frustums, (int|ext)insics for relative pos encoding

Alexandre Morgand

17,818 Aufrufe • vor 11 Monaten

MAC-VO: Metrics-Aware Covariance for Learning-based Stereo Visual Odometry TL;DR: learning-based stereo; learned metrics-aware matching uncertainty for dual purposes: selecting keypoint and weighing the residual in pose graph optimization.

MAC-VO: Metrics-Aware Covariance for Learning-based Stereo Visual Odometry TL;DR: learning-based stereo; learned metrics-aware matching uncertainty for dual purposes: selecting keypoint and weighing the residual in pose graph optimization.

Alexandre Morgand

17,367 Aufrufe • vor 1 Jahr

LookCloser🔍: Frequency-aware Radiance Field for Tiny-Detail Scene TL;DR: FA-NeRF:l frequency-aware framework for view synthesis that simultaneously captures the overall scene structure and high-definition details within a single NeRF model.

LookCloser🔍: Frequency-aware Radiance Field for Tiny-Detail Scene TL;DR: FA-NeRF:l frequency-aware framework for view synthesis that simultaneously captures the overall scene structure and high-definition details within a single NeRF model.

Alexandre Morgand

16,201 Aufrufe • vor 1 Jahr

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