Datasets:

astralhf
/

yonder

@@ -14,13 +14,13 @@ task_categories:
 - depth-estimation
 - robotics
 size_categories:
-- 1M<n<10M
-pretty_name: "Yonder: A 6.1M-Frame Drone Navigation Dataset"
 language:
 - en
 ---
-# Yonder: A 6.1M-Frame Drone-Perspective Dataset for Indoor Navigation
 > **The cross-simulator generalization gap.**
 > Yonder is the largest publicly available drone-perspective dataset for indoor
@@ -29,16 +29,15 @@ language:
 > cleanly to a different simulator, even when both target the same task.
 This dataset accompanies the NeurIPS 2026 Datasets & Benchmarks submission:
-*"Yonder: A 6.1M-Frame Drone Navigation Dataset and the Cross-Simulator Generalization Gap."*
-## Headline numbers
-- **6,118,356** drone-perspective frames
-- **509,863** waypoint NPZ files (one per waypoint × yaw)
-- **251** indoor 3D environments
 - **52 sensor arrays** per NPZ (stereo RGB, depth, IR, LiDAR-360, semantic segmentation, pose, IMU)
-- **92 environments** with semantic annotations
-- **~3.8 TB** total
 ## What's in a waypoint
@@ -53,23 +52,23 @@ Every waypoint NPZ contains a single drone pose with **12 yaw orientations**. Fo
 | Up IR / Down IR | 640×480, uint8 |
 | LiDAR-360 | 1024 × 16 channel, float32 (meters) |
 | Position / Orientation / IMU | float32 (Habitat-Sim world frame) |
-| Semantic segmentation | 640×480 instance + class IDs (92 scenes only) |
 ## Source environments
-Yonder is rendered from two open-source 3D scene datasets, both retained for their
-permissive licenses:
 | Source | License | Scenes | Waypoints | Has Semantics |
 |---|---|---:|---:|---|
-| [HSSD](https://huggingface.co/datasets/hssd/hssd-hab) (Habitat Synthetic Scenes Dataset) | CC-BY-NC-4.0 | 167 | 387,527 | Yes |
-| [ReplicaCAD](https://aihabitat.org/datasets/replica_cad/) | CC-BY-4.0 | 84 | 122,336 | No |
-| **Total** | | **251** | **509,863** | **92 with semantics** |
-> HM3D and Replica scenes were excluded from the release because their upstream
-> licenses (Matterport academic EULA and Meta research-only terms respectively) do
-> not permit open redistribution of derivative renders. **Yonder ships its own
-> rendered observations only — no upstream meshes are redistributed.**
 ## License
@@ -77,22 +76,13 @@ permissive licenses:
   inheriting HSSD's NonCommercial restriction. HSSD attribution preserved per source license.
 - **Code, model checkpoints, benchmark:** Apache-2.0 (see linked code repo).
-If you build solely on the ReplicaCAD-derived subset (84 scenes / 122,336 waypoints),
-that subset is dual-traceable to CC-BY-4.0 and may be used commercially with attribution.
 ## Quick start
 ```python
-from datasets import load_dataset
 import numpy as np
-# Stream a single waypoint
-ds = load_dataset("astralhf/yonder", split="train", streaming=True)
-sample = next(iter(ds))
-print(sample.keys())  # 52+ sensor arrays per waypoint
-# Or download a single scene directly
-from huggingface_hub import snapshot_download
 path = snapshot_download(
     repo_id="astralhf/yonder",
     repo_type="dataset",
@@ -100,9 +90,9 @@ path = snapshot_download(
 )
 # Load a waypoint
-data = np.load(f"{path}/indoor/drone-data/augmented/hssd-102343992/wp0000.npz")
-left_rgb_yaw0 = data["left_rgb_yaw00"]    # shape (480, 640, 3)
-forward_depth_yaw0 = data["forward_depth_yaw00"]  # shape (480, 640) float16
 lidar = data["lidar360"]                  # shape (1024, 16) float32
 ```
@@ -111,29 +101,69 @@ lidar = data["lidar360"]                  # shape (1024, 16) float32
 For NeurIPS reviewers and others who want a small smoke-test before downloading
 multiple TB, see the companion subset:
 **[`astralhf/yonder-sample`](https://huggingface.co/datasets/astralhf/yonder-sample)**
-(~10 GB, one HSSD scene with semantics, all 12 yaws per waypoint).
-## Dataset structure
 ```
-indoor/drone-data/augmented/
 ├── hssd-102343992/
 │   ├── manifest.json
-│   ├── wp0000.npz
-│   ├── wp0001.npz
-│   └── ...
-├── hssd-102344022/
 │   └── ...
-└── replica-cad-apt_0/
-    └── ...
 ```
-Each scene directory contains:
-- `manifest.json` — scene-level metadata (source, source_id, scene MD5, license note,
-  navmesh extents, waypoint sampling parameters).
-- `wp####.npz` — one NPZ file per waypoint, each holding 12 yaws across all sensor
   modalities.
 ## Splits
 Yonder is released without pre-defined train/val/test splits. The paper's experiments
@@ -158,7 +188,7 @@ the paper for the exact split file (also released alongside the code).
   closed-loop counterpart, may not reflect deployment performance.
 🚫 **Not for:**
-- Commercial use (the HSSD-derived majority subset is CC-BY-NC).
 - Surveillance, biometric identification, or any application of open-vocabulary
   detection to identify specific real persons. The simulated scenes contain no
   real persons; transfer to person-identification tasks is out of scope and
@@ -166,15 +196,14 @@ the paper for the exact split file (also released alongside the code).
 ## Responsible AI considerations
-- **No real persons.** Yonder is rendered entirely from synthetic 3D scenes
-  (HSSD, ReplicaCAD); no humans are present in any frame. No PII, no biometric
-  data, no faces.
 - **Synthetic-only domain.** Performance on Yonder does not transfer to real
   imagery without explicit sim-to-real treatment. Anyone deploying perception
   trained on Yonder in the real world must perform their own real-domain validation.
-- **Geographic / cultural bias.** HSSD and ReplicaCAD scenes are biased toward
-  Western residential interiors. Models trained on Yonder may underperform on
-  interior styles outside this distribution.
 - **Cross-simulator evaluation is mandatory.** The dataset's primary contribution
   is making it easy to discover that fine-tuning gains can be illusory.
   Models reported on Yonder should be validated in a different simulator (or
@@ -187,7 +216,7 @@ RAI fields.
 ```bibtex
 @inproceedings{anonymous2026yonder,
-  title  = {Yonder: A 6.1M-Frame Drone Navigation Dataset and the Cross-Simulator Generalization Gap},
   author = {Anonymous Author(s)},
   booktitle = {Advances in Neural Information Processing Systems (Datasets and Benchmarks Track)},
   year   = {2026},
@@ -202,5 +231,9 @@ review, the camera-ready version will list authors and contact information here.
 ## Changelog
-- **2026-05-01** — Initial release: 251 scenes (167 HSSD + 84 ReplicaCAD).
-  HM3D and Replica subsets removed prior to release for license compatibility.

 - depth-estimation
 - robotics
 size_categories:
+- 100K<n<1M
+pretty_name: "Yonder: A 4.65M-Frame Drone Navigation Dataset"
 language:
 - en
 ---
+# Yonder: A 4.65M-Frame Drone-Perspective Dataset for Indoor Navigation
 > **The cross-simulator generalization gap.**
 > Yonder is the largest publicly available drone-perspective dataset for indoor
 > cleanly to a different simulator, even when both target the same task.
 This dataset accompanies the NeurIPS 2026 Datasets & Benchmarks submission:
+*"Yonder: A 4.65M-Frame Drone Navigation Dataset and the Cross-Simulator Generalization Gap."*
+## Headline numbers (paper subset)
+- **4,650,324** drone-perspective frames
+- **387,527** waypoint NPZ files (one per waypoint × 12 yaws)
+- **167** indoor 3D environments (all from HSSD, all with semantic annotations)
 - **52 sensor arrays** per NPZ (stereo RGB, depth, IR, LiDAR-360, semantic segmentation, pose, IMU)
+- **~3.3 TB** total
 ## What's in a waypoint
 | Up IR / Down IR | 640×480, uint8 |
 | LiDAR-360 | 1024 × 16 channel, float32 (meters) |
 | Position / Orientation / IMU | float32 (Habitat-Sim world frame) |
+| Semantic segmentation | 640×480 instance + class IDs (all 167 scenes) |
 ## Source environments
+Yonder is rendered from a single open-source 3D scene dataset:
 | Source | License | Scenes | Waypoints | Has Semantics |
 |---|---|---:|---:|---|
+| [HSSD](https://huggingface.co/datasets/hssd/hssd-hab) (Habitat Synthetic Scenes Dataset) | CC-BY-NC-4.0 | 167 | 387,527 | 167 of 167 |
+> Earlier collection passes also covered ReplicaCAD (84 scenes, CC-BY-4.0, no semantics),
+> Replica (Meta research-only terms), and HM3D (Matterport academic EULA). Replica and
+> HM3D were excluded because their upstream licenses do not permit open redistribution
+> of derivative renders. ReplicaCAD was excluded because it lacks semantic annotations
+> and was not used in any reported experiment, in service of a single-source,
+> fully-experiment-relevant artifact. **Yonder ships its own rendered observations only —
+> no upstream meshes are redistributed.**
 ## License
   inheriting HSSD's NonCommercial restriction. HSSD attribution preserved per source license.
 - **Code, model checkpoints, benchmark:** Apache-2.0 (see linked code repo).
 ## Quick start
 ```python
+from huggingface_hub import snapshot_download
 import numpy as np
+# Download a single scene
 path = snapshot_download(
     repo_id="astralhf/yonder",
     repo_type="dataset",
 )
 # Load a waypoint
+data = np.load(f"{path}/indoor/drone-data/augmented/hssd-102343992/hssd-102343992_wp0000.npz")
+left_rgb_yaw0 = data["yaw000_left_rgb"]    # shape (480, 640, 3)
+forward_depth_yaw0 = data["yaw000_forward_depth"]  # shape (480, 640) float16
 lidar = data["lidar360"]                  # shape (1024, 16) float32
 ```
 For NeurIPS reviewers and others who want a small smoke-test before downloading
 multiple TB, see the companion subset:
 **[`astralhf/yonder-sample`](https://huggingface.co/datasets/astralhf/yonder-sample)**
+(~500 MB, one HSSD scene, all 12 yaws per waypoint).
+## Repository layout
 ```
+indoor/drone-data/augmented/         ← paper's primary subset (4.65M frames)
 ├── hssd-102343992/
 │   ├── manifest.json
+│   ├── hssd-102343992_wp0000.npz
 │   └── ...
+└── hssd-*/                          (167 scene dirs)
+annotations/                         ← COCO-format detection labels
+└── hssd-*/
+    ├── annotations.json             (per-scene bbox annotations)
+    └── object_inventory.json        (per-scene object catalog)
+indoor/isaac-sim-native/             ← cross-simulator evaluation subset
+├── scenes/                          (60 Isaac-rendered indoor scenes)
+└── annotations/
+outdoor/                             ← sibling resources (not part of the NeurIPS paper)
+├── boreal/  coastal/  desert/  forest/  lunar/
+├── infinigen/                       (procedural Infinigen scenes)
+├── carla-cities/                    (8 CARLA towns, full UE4 city geometry)
+└── carla-roads/                     (8 CARLA towns, drivable surface only)
 ```
+Each scene directory under `indoor/drone-data/augmented/` contains:
+- `manifest.json` — scene-level metadata (scene_id, sampling parameters, total_waypoints,
+  total_frames, unique_object_ids).
+- `<scene_id>_wp####.npz` — one NPZ file per waypoint, each holding 12 yaws across all sensor
   modalities.
+## Cross-simulator evaluation subset (`indoor/isaac-sim-native/`)
+Yonder's central thesis — that perception trained on one simulator does not transfer
+cleanly to another — requires a different-simulator evaluation set. We provide
+**60 Isaac-rendered indoor scenes** (warehouse, hospital, office variants) under
+`indoor/isaac-sim-native/scenes/`, with companion annotations under
+`indoor/isaac-sim-native/annotations/`. These scenes are used for closed-loop
+navigation evaluation in the paper.
+## Sibling resources (not part of the NeurIPS paper)
+The repository also hosts outdoor scene assets for separate research not described
+in the Yonder paper. These are USD scene geometry (different schema from the indoor
+waypoint NPZs):
+- `outdoor/{boreal,coastal,desert,forest,lunar}/` — biome-specific scenes with
+  per-biome `previews/`, `prototypes/`, and `scenes/` directories.
+- `outdoor/infinigen/` — procedural scenes generated with [Infinigen](https://infinigen.org/),
+  16 scenes spanning canyon, coast, desert, forest, mountain biomes.
+- `outdoor/carla-cities/` — full UE4 city geometry from CARLA's 8 towns,
+  ~14k mesh instances total. Open in Isaac Sim with
+  `omni.usd.get_context().open_stage("outdoor/carla-cities/Town03/scene.usd")`.
+- `outdoor/carla-roads/` — drivable-surface USD only, derived from CARLA OpenDRIVE
+  (MIT-licensed). 8 towns, plus 380k+ semantic axis-aligned bboxes per town.
+These outdoor resources are governed by their respective upstream licenses (CARLA: MIT;
+Infinigen: BSD-3-Clause). They are **not** part of the NeurIPS paper's claims and
+should be evaluated against their own licenses if used.
 ## Splits
 Yonder is released without pre-defined train/val/test splits. The paper's experiments
   closed-loop counterpart, may not reflect deployment performance.
 🚫 **Not for:**
+- Commercial use (the entire dataset inherits HSSD's CC-BY-NC restriction).
 - Surveillance, biometric identification, or any application of open-vocabulary
   detection to identify specific real persons. The simulated scenes contain no
   real persons; transfer to person-identification tasks is out of scope and
 ## Responsible AI considerations
+- **No real persons.** Yonder is rendered entirely from synthetic 3D scenes (HSSD);
+  no humans are present in any frame. No PII, no biometric data, no faces.
 - **Synthetic-only domain.** Performance on Yonder does not transfer to real
   imagery without explicit sim-to-real treatment. Anyone deploying perception
   trained on Yonder in the real world must perform their own real-domain validation.
+- **Geographic / cultural bias.** HSSD scenes are biased toward Western residential
+  interiors. Models trained on Yonder may underperform on interior styles outside
+  this distribution.
 - **Cross-simulator evaluation is mandatory.** The dataset's primary contribution
   is making it easy to discover that fine-tuning gains can be illusory.
   Models reported on Yonder should be validated in a different simulator (or
 ```bibtex
 @inproceedings{anonymous2026yonder,
+  title  = {Yonder: A 4.65M-Frame Drone Navigation Dataset and the Cross-Simulator Generalization Gap},
   author = {Anonymous Author(s)},
   booktitle = {Advances in Neural Information Processing Systems (Datasets and Benchmarks Track)},
   year   = {2026},
 ## Changelog
+- **2026-05-01** — Initial release: 167 HSSD scenes / 387,527 waypoints / 4.65M frames /
+  semantic annotations for all 167. HM3D, Replica, and ReplicaCAD subsets removed prior
+  to release (HM3D and Replica for license incompatibility; ReplicaCAD for lacking
+  semantic annotations and not being used in any reported experiment). Three Habitat
+  test scenes (apartment_1, skokloster-castle, van-gogh-room) also excluded for
+  upstream-license incompatibility.

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