---
title: "LoGeR"
description: "LoGeR: 3d-reconstruction and trajectory; Verified."
modelId: "loger"
pageSource: generated
---

LoGeR reconstructs 3D scenes with camera trajectories and point clouds from input views, and is one of the verified 3D routes in this catalog: checkpoint-backed Studio inference produced finite poses, depth, and a 601,570-vertex point cloud, with evidence in inference_evidence.yaml.

<ModelPaperFigures modelId="loger" locale="en" />

The recorded paper is [arXiv 2603.03269](https://arxiv.org/abs/2603.03269).

Project page: [LoGeR-project.github.io](https://LoGeR-project.github.io/). Code: [Junyi42/LoGeR](https://github.com/Junyi42/LoGeR).

<ModelCommandBuilder modelId="loger" locale="en" />

## What it is for

Pick `loger` for feed-forward geometry: views in, reconstruction / trajectory / point cloud out. Use it when you need the catalog 3D route rather than a depth-only prior.

The catalog records a reconstruction-plus-trajectory model exporting binary PLY artifacts; the publishing institution and architecture internals are not recorded in this repository (upstream: Junyi42/LoGeR, apache-2.0).

Catalog tasks include 3d-reconstruction, trajectory, and point-cloud. Documented outputs include point cloud.

## Runtime contract

Optional `input_path`, `interactions`, `task_type`, `camera_view`, and `visualize_ops`; artifacts `result.ply`.

CLI task profiles: `interactive-video`. WorldFoundry binds `LoGeRPipeline`.

Family status: **Verified**.

Verified end to end in the shared worldfoundry-unified-cu128 environment — a dependable choice for point-cloud navigation pipelines.

In-tree LoGeR point-cloud navigation pipeline is registered for reconstruction and trajectory rendering.

## Running in WorldFoundry

The catalog launch is `worldfoundry-eval run loger --pipeline.task-profile interactive-video`. The command builder above switches `--pipeline.task-profile` among recorded tasks and still emits `worldfoundry-eval run`.

It runs in the unified environment `worldfoundry-unified-cu128` (Python 3.11, CUDA 12.8).

Recorded weight repositories include `Junyi42/LoGeR`. Prepare the environment and check local assets with `bash scripts/inference/prepare_model_infer.sh loger`. Add `--download` to fetch missing public checkpoints.

Status: **Verified**.

<ModelRelatedRecipes modelId="loger" locale="en" />