Papers › Multi-Attribute Interactions Matter for 3D Visual Grounding

Multi-Attribute Interactions Matter for 3D Visual Grounding

1 Jan 2024CVPR 2024 1archive 2025-07-28

Can Xu, Yuehui Han, Rui Xu, Le Hui, Jin Xie, Jian Yang

3D visual grounding aims to localize 3D objects described by free-form language sentences. Following the detection-then-matching paradigm existing methods mainly focus on embedding object attributes in unimodal feature extraction and multimodal feature fusion to enhance the discriminability of the proposal feature for accurate grounding. However most of them ignore the explicit interaction of multiple attributes causing a bias in unimodal representation and misalignment in multimodal fusion. In this paper we propose a multi-attribute aware Transformer for 3D visual grounding learning the multi-attribute interactions to refine the intra-modal and inter-modal grounding cues. Specifically we first develop an attribute causal analysis module to quantify the causal effect of different attributes for the final prediction which provides powerful supervision to correct the misleading attributes and adaptively capture other discriminative features. Then we design an exchanging-based multimodal fusion module which dynamically replaces tokens with low attribute attention between modalities before directly integrating low-dimensional global features. This ensures an attribute-level multimodal information fusion and helps align the language and vision details more efficiently for fine-grained multimodal features. Extensive experiments show that our method can achieve state-of-the-art performance on ScanRefer and Sr3D/Nr3D datasets.

PaperPDFCode

Code

volcanoxc/ma2transvg officialmentioned in paperpytorchnot reachable when probed 2026-09-18 — repositories for recent papers often appear after camera-ready report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

3D visual groundingAttributeVisual Grounding

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

ALIGNAWAREAbsolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutFocusLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections