Papers › See It All: Contextualized Late Aggregation for 3D Dense Captioning
See It All: Contextualized Late Aggregation for 3D Dense Captioning
Minjung Kim, Hyung Suk Lim, Seung Hwan Kim, Soonyoung Lee, Bumsoo Kim, Gunhee Kim
3D dense captioning is a task to localize objects in a 3D scene and generate descriptive sentences for each object. Recent approaches in 3D dense captioning have adopted transformer encoder-decoder frameworks from object detection to build an end-to-end pipeline without hand-crafted components. However, these approaches struggle with contradicting objectives where a single query attention has to simultaneously view both the tightly localized object regions and contextual environment. To overcome this challenge, we introduce SIA (See-It-All), a transformer pipeline that engages in 3D dense captioning with a novel paradigm called late aggregation. SIA simultaneously decodes two sets of queries-context query and instance query. The instance query focuses on localization and object attribute descriptions, while the context query versatilely captures the region-of-interest of relationships between multiple objects or with the global scene, then aggregated afterwards (i.e., late aggregation) via simple distance-based measures. To further enhance the quality of contextualized caption generation, we design a novel aggregator to generate a fully informed caption based on the surrounding context, the global environment, and object instances. Extensive experiments on two of the most widely-used 3D dense captioning datasets demonstrate that our proposed method achieves a significant improvement over prior methods.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D dense captioning | ScanRefer Dataset | See It All | BLEU-4 | 42.17 | #2 of 12 | Archive leaderboard | report |
| 3D dense captioning | ScanRefer Dataset | See It All | CIDEr | 83.14 | #2 of 12 | Archive leaderboard | report |
| 3D dense captioning | ScanRefer Dataset | See It All | METEOR | 27.92 | #2 of 12 | Archive leaderboard | report |
| 3D dense captioning | ScanRefer Dataset | See It All | ROUGE-L | 59.44 | #2 of 12 | 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
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