Papers › SGAligner : 3D Scene Alignment with Scene Graphs

SGAligner : 3D Scene Alignment with Scene Graphs

28 Apr 2023arXiv:2304.14880archive 2025-07-28

Sayan Deb Sarkar, Ondrej Miksik, Marc Pollefeys, Daniel Barath, Iro Armeni

Building 3D scene graphs has recently emerged as a topic in scene representation for several embodied AI applications to represent the world in a structured and rich manner. With their increased use in solving downstream tasks (eg, navigation and room rearrangement), can we leverage and recycle them for creating 3D maps of environments, a pivotal step in agent operation? We focus on the fundamental problem of aligning pairs of 3D scene graphs whose overlap can range from zero to partial and can contain arbitrary changes. We propose SGAligner, the first method for aligning pairs of 3D scene graphs that is robust to in-the-wild scenarios (ie, unknown overlap -- if any -- and changes in the environment). We get inspired by multi-modality knowledge graphs and use contrastive learning to learn a joint, multi-modal embedding space. We evaluate on the 3RScan dataset and further showcase that our method can be used for estimating the transformation between pairs of 3D scenes. Since benchmarks for these tasks are missing, we create them on this dataset. The code, benchmark, and trained models are available on the project website.

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Embedding sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant fingerprinted MIT (permissive) · b1dbe3c3e8514beb · report
MultiGAT sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant MIT (permissive) · a9b3588718c4a5eb · report
MultiModalFusion sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: well formed MIT (permissive) · c1e540367f0b88cd · report
NaivePCT sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant fingerprinted MIT (permissive) · bcf1c7281fec9b0f · report
SA sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant fingerprinted MIT (permissive) · 2a7653fcd1586778 · report
STN3d sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant fingerprinted MIT (permissive) · 8b723461b4045828 · report
STNkd sayands/sgaligner/src/aligner/sg_aligner.py official repository ran · metamorphic tier: invariant fingerprinted MIT (permissive) · 7bdfb2479e4f7a3e · report
BaseNetwork sayands/sgaligner/src/aligner/sg_aligner.py official repository unverified MIT (permissive) · a7f3284931ce23a3 · report
MultiModalEncoder sayands/sgaligner/src/aligner/sg_aligner.py official repository unverified MIT (permissive) · a1845bb6689c837a · report
PointNetfeat sayands/sgaligner/src/aligner/sg_aligner.py official repository unverified MIT (permissive) · fdc7a053313b0a64 · report

Tasks

3D Scene Graph AlignmentContrastive LearningKnowledge GraphsPoint Cloud Registration

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Scene Graph Alignment 3DSSG SGAligner F1 89.3 #2 of 2 Archive leaderboard report
3D Scene Graph Alignment 3DSSG SGAligner Hits@1 94.3 #2 of 2 Archive leaderboard report
3D Scene Graph Alignment 3DSSG SGAligner MRR 96.3 #2 of 2 Archive leaderboard report
Point Cloud Registration 3RScan SGAligner CD 0.0111 #2 of 2 Archive leaderboard report
Point Cloud Registration 3RScan SGAligner RRE 1.012 #2 of 2 Archive leaderboard report
Point Cloud Registration 3RScan SGAligner RTE 1.67 #2 of 2 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Contrastive LearningGAT

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