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Alexandre Morgand

@Almorgand • 2,410 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

"SAM2Matting: Generalized Image and Video Matting" TL;DR: upgrades foundation video trackers like SAM2 into state-of-the-art image and video matting models by decoupling temporal tracking from fine-grained alpha estimation achieving zero-shot video matting without video training

"SAM2Matting: Generalized Image and Video Matting" TL;DR: upgrades foundation video trackers like SAM2 into state-of-the-art image and video matting models by decoupling temporal tracking from fine-grained alpha estimation achieving zero-shot video matting without video training

24,903 просмотров

"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

34,544 просмотров

Videos

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"AgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos" VLM agent+optimization to reconstruct an object geometry+kinematic structure from RGB video. Pose+articulation through time including occlusions, transparent objects. No dense pixel correspondences.

"AgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos" VLM agent+optimization to reconstruct an object geometry+kinematic structure from RGB video. Pose+articulation through time including occlusions, transparent objects. No dense pixel correspondences.

Alexandre Morgand

25,126 просмотров • 1 месяц назад

"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

43,375 просмотров • 4 месяцев назад

"Fast Foundation Stereo: When Foundation Models Meet Efficient Stereo Matching" TL;DR: distills stereo foundation models into an efficient real-time stereo matching framework, preserving high accuracy while dramatically reducing inference cost.

"Fast Foundation Stereo: When Foundation Models Meet Efficient Stereo Matching" TL;DR: distills stereo foundation models into an efficient real-time stereo matching framework, preserving high accuracy while dramatically reducing inference cost.

Alexandre Morgand

14,854 просмотров • 3 месяцев назад

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

60,773 просмотров • 1 год назад

"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

13,807 просмотров • 5 месяцев назад

"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

11,958 просмотров • 4 месяцев назад

"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

15,192 просмотров • 8 месяцев назад

"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 просмотров • 7 месяцев назад

"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

17,837 просмотров • 1 год назад

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 просмотров • 1 год назад

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 просмотров • 1 год назад

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