CrossRealityMesh: Importing and Interacting with Real-World Objects in Virtual Reality
Bibliographic record
Abstract
When wearing a head-mounted display, users are typically unable to see or interact with the physical world. We explore the potential of enabling interaction with real-world items in VR, opening possibilities for education, work, entertainment, and beyond. We present CrossRealityMesh: a system where users can create custom-shaped passthrough meshes—"windows" into the real world—that allow users to see items from the real world, and the meshes follow the items when moved. In a mixed-methods study (n = 24), participants used the system across four interactive scenarios, importing and using a mug, laptop, whiteboard, and tools in VR. Our participants found CrossRealityMesh exciting, valuable, and fun, and demonstrated its effectiveness in importing and interacting with real-world items in VR in diverse scenarios. Their workflows and feedback also suggested that passthrough meshes need not precisely match the item’s shape, indicating that visual accuracy is not always necessary for effective cross-reality interaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".