| --- |
| license: cc-by-nc-4.0 |
| pretty_name: Something's Missing Here |
| size_categories: |
| - n<1K |
| task_categories: |
| - image-classification |
| tags: |
| - change-detection |
| - missing-object-detection |
| - image-pairs |
| - siamese |
| --- |
| |
| # Something's Missing Here |
|
|
| A dataset of viewpoint-aligned before/after image pairs for training and |
| evaluating missing-object detection: each pair shows the same scene from |
| (nearly) the same viewpoint, once with one or more objects present and once |
| after they were removed, with a label naming what went missing. |
|
|
| The dataset originated from pairs derived from the |
| [simkoc/Remove360](https://huggingface.co/datasets/simkoc/Remove360) dataset |
| (`training/Remove360_based/`), extended with original photographs collected |
| by the dataset author (`training/DeTaken/`), plus a held-out `test/` split of |
| scenes that appear nowhere in training. A separate `challenging/` split |
| holds harder cases — object swaps, replacements, and rearrangements — where |
| telling "something is missing" apart from "things merely changed" takes |
| more than spotting a difference (see below). |
|
|
| ## Structure |
|
|
| Both splits are organized by collection, then scene, then pair: |
|
|
| ``` |
| training/ |
| ├── DeTaken/ original photographs by the dataset author |
| │ └── <scene>/ bullseye, cabinet_window, corner_table, michal_01, |
| │ └── pair_<nn>/ shay_01, vases, ... |
| │ ├── before.jpg earlier image |
| │ ├── after.jpg later image |
| │ └── label.json {"missing": true, "items": ["<removed object>"]} |
| │ or {"missing": false, "items": []} for no-change pairs |
| └── Remove360_based/ pairs derived from Remove360 (see below) |
| └── <scene>/ backyard_big_tree, backyard_stones, park, |
| └── pair_<nn>/ stairwell |
| test/ |
| ├── DeTaken/ held-out scenes, never in training |
| │ └── test_<scene>/ test_class_01, test_class_02, test_class_03 |
| │ └── pair_<nn>/ |
| └── Remove360_based/ held-out Remove360 scenes, never in training |
| └── test_<scene>/ test_backyard_bricks, test_backyard_toys, |
| └── pair_<nn>/ test_bedroom, test_living-room, test_office |
| challenging/ harder cases: swaps, replacements, rearrangements |
| ├── training/ |
| │ └── <scene>/ same scene names as training/DeTaken |
| │ └── pair_<nn>/ |
| └── test/ |
| └── pair_<nn>/ held-out challenging pairs (flat) |
| ``` |
|
|
| **Size in pairs: 350 training and 116 test** (across 32 and 8 scenes |
| respectively), plus 93 challenging pairs (81 training, 12 test) — 559 pairs |
| in total. Breakdown (crop-shift = synthetic no-change pairs, see below): |
|
|
| | split | collection | scenes | pairs | positive | negative | of which crop-shift | |
| |---|---|---|---|---|---|---| |
| | training | DeTaken | 28 | 254 | 104 | 150 | 116 | |
| | training | Remove360_based | 4 | 96 | 48 | 48 | 48 | |
| | test | DeTaken | 3 | 40 | 21 | 19 | 0 | |
| | test | Remove360_based | 5 | 76 | 76 | 0 | 0 | |
| | challenging | training | 17 | 81 | 27 | 54 | 0 | |
| | challenging | test | 1 | 12 | 6 | 6 | 0 | |
|
|
| **Test pairs are unmanipulated.** Synthetic pairs are confined to |
| `training/`: every pair in `test/` and `challenging/` consists of two |
| genuinely captured photographs, with all removals physical — nothing was |
| digitally added to, removed from, or composited into any image. Verified |
| against the folder tree: no test `label.json` carries a `source` field |
| (the marker of a derived pair), the crop-shift count is zero across all |
| test splits, and pair folders contain nothing but `before.jpg`, |
| `after.jpg`, and `label.json`. The only processing applied to test images |
| is the disclosed geometric viewpoint alignment of the `Remove360_based` |
| subset (a homography warp and crop — see below). |
|
|
| Negative pairs that were derived rather than photographed carry a `source` |
| field in `label.json` documenting what they were built from. |
|
|
| ## Crop-shift negatives |
|
|
| Many scenes were photographed only with something removed, leaving no |
| "nothing changed" pairs to learn from. Those scenes are supplemented with |
| **crop-shift negatives**: both images of the pair are crops of the *same* |
| photograph, taken at different offsets — one window trimmed at the right and |
| top edges, the other trimmed by the same amounts at the bottom and left. The |
| content is therefore identical and only the framing moves, which is exactly |
| the "the camera shifted, the scene did not" case a removal detector must not |
| mistake for a disappearance. |
|
|
| Two negatives are generated per source pair (one from its `before.jpg`, one |
| from its `after.jpg`; the `Remove360_based` scenes retain only one of the |
| two), the trim is 10–20 px per axis, both crops come out the same size, and |
| each carries |
| `{"missing": false, "items": [], "source": "crop-shift of <pair>/<file>"}`. |
|
|
| They are cheap and plentiful, but they only vary translation — unlike real |
| re-shot no-change pairs, the lighting, focus, and perspective are identical. |
| Treat them as a supplement: the `crop-shift` column above shows how much of |
| each split's negative set is synthetic. Crop-shift pairs exist only in |
| `training/` — the `test/` and `challenging/` splits contain none, so a |
| model that has merely learned "small shift ⇒ nothing missing" shows up |
| there as false alarms. |
|
|
| In `Remove360_based/` pairs (both splits), `before.jpg` is warped into |
| `after.jpg`'s camera frame and both images are cropped to their shared valid |
| region, so the two images are pixel-aligned with identical dimensions. |
| `DeTaken/` and `challenging/` pairs are handheld re-shots from approximately |
| the same viewpoint and are not pixel-aligned. The `class_*` / `test_class_*` |
| scenes are tabletop object arrangements shot in rapid succession (seconds |
| apart), with roughly half of each scene being no-change negative pairs. |
|
|
| ## The challenging split |
|
|
| `challenging/` holds the deliberately hard cases, separated from the main |
| splits so models can be trained and evaluated with or without them. In the |
| main splits, the change between `before` and `after` is a clean object |
| removal (or nothing at all) seen under a small viewpoint change. In |
| `challenging/`, other things happen too — objects are **swapped** with one |
| another, **replaced** by different objects, or **rearranged** within the |
| scene: |
|
|
| - Its **negatives** (`missing: false`, the majority here) are hard: items |
| moved, swapped, or substituted — the scene visibly changed, yet nothing |
| went missing. A model leaning on "the images differ, so something is |
| gone" fails these. |
| - Its **positives** (`missing: true`) hide a genuine removal among such |
| distractions, so spotting the difference is not enough — the model must |
| identify that the change is specifically a disappearance. |
|
|
| Labels use the same `label.json` format. `challenging/test/` pairs are held |
| out from all training and sit directly under the folder (no scene |
| subfolders). |
|
|
| ## The Remove360_based subset |
| |
| [Remove360](https://huggingface.co/datasets/simkoc/Remove360) provides |
| separate pre-removal and post-removal camera walks of real indoor and |
| outdoor scenes. Its before and after images are independent captures — they |
| are **not** pixel-aligned pairs — so this subset was built by finding and |
| aligning the closest matching viewpoints between the two walks. |
| |
| 172 pairs — 124 positives (something was removed) and 48 crop-shift |
| negatives — across 9 scenes and 9 removed objects, divided by whole scene |
| into `training/` (4 scenes, 96 pairs, one crop-shift negative per positive) |
| and the held-out `test/` (5 scenes, 76 pairs, positives only, prefixed |
| `test_`). Remove360's single large backyard scene is split into four |
| sub-scenes by area (big tree lawn, brick patio, stones, toy corner): |
|
|
| | scene | positive | negative | | removed object | pairs | |
| |---|---|---|---|---|---| |
| | stairwell | 24 | 24 | | chairs | 36 | |
| | test_backyard_toys | 23 | 0 | | backpack | 24 | |
| | test_living-room | 21 | 0 | | stroller | 16 | |
| | test_backyard_bricks | 16 | 0 | | sofa | 15 | |
| | test_office | 13 | 0 | | deckchair | 11 | |
| | backyard_big_tree | 11 | 11 | | bicycle | 10 | |
| | park | 10 | 10 | | pillows | 6 | |
| | test_bedroom | 3 | 0 | | table | 3 | |
| | backyard_stones | 3 | 3 | | toy-truck | 3 | |
|
|
| ### How it was generated |
|
|
| 1. **Download** — the full `simkoc/Remove360` repository (file tree of |
| `<scene>/<object>/train|test|masks`), where `train/` holds pre-removal |
| ("before") images and `test/` holds post-removal ("after") images. |
| 2. **Valid-region cropping** — a subset of Remove360's images is truncated |
| at fixed byte boundaries on the Hub itself (all of `backyard/stroller` at |
| 2.75 MiB, all of `backyard/playhouse` at 256 KiB); truncated JPEGs decode |
| with a uniform gray tail. Each image was cropped to its real content |
| before matching, and images with less than 15% real content were |
| discarded. |
| 3. **Viewpoint matching** — every after image was ranked against all before |
| images of the same object by SIFT feature matches (Lowe ratio 0.75); the |
| top 3 candidates were verified with a RANSAC homography (reprojection |
| threshold 4 px, minimum 40 inliers). |
| 4. **Acceptance criteria** — a pair was kept only if each frame covers at |
| least **85%** of the other under the homography (mutual frame coverage) |
| and the warped before image correlates with the after image at |
| **≥ 0.475** zero-mean normalized correlation. Each before image was used |
| in at most one pair. |
| 5. **Alignment and cropping** — the accepted before image was warped into |
| the after frame at full resolution and both images were cropped to the |
| largest rectangle of shared valid pixels. |
| 6. **Labeling** — each pair's `label.json` records the removed object (the |
| Remove360 object folder the pair came from) as |
| `{"missing": true, "items": ["<object>"]}`. |
| 7. **Manual curation** — the automatically accepted pairs were reviewed and |
| some were deleted by hand; the remaining pairs were renumbered |
| contiguously. |
| 8. **No-change negatives** — this subset's negatives are the crop-shift |
| pairs described above, kept only in the training scenes (one per |
| positive); the test scenes hold positives only. An earlier approach paired |
| same-walk images (two pre-removal frames, or two post-removal frames, |
| matched with the same gates as the positives) and a few such pairs may |
| remain; their `label.json` `source` field names the two images they came |
| from. |
|
|
| ### Known limitations |
|
|
| - **No `playhouse` pairs** — all of Remove360's `backyard/playhouse` images |
| are truncated to ~6% of their content on the Hub, which is below the |
| usability floor. |
| - **Stroller pairs are half-height** — `backyard/stroller` images are |
| truncated to roughly their top half, so its pairs are wide bands |
| (~3900×1000) rather than full frames (~4000×2200). |
| - **Residual parallax** — alignment uses a single homography per pair; small |
| parallax between the two camera positions can remain, especially on |
| close foreground geometry. |
| - Some objects other than the labeled one may have shifted slightly between |
| Remove360's two capture sessions. |
|
|
| ## License and attribution |
|
|
| The `Remove360_based/` subset is a derivative of |
| [simkoc/Remove360](https://huggingface.co/datasets/simkoc/Remove360) and is |
| distributed under the same **CC-BY-NC-4.0** license, which this dataset |
| adopts as a whole. If you use it, please also cite the original Remove360 |
| paper ([arXiv:2508.11431](https://arxiv.org/abs/2508.11431)). |
|
|
