3D scene-centric VLMs underutilize the 3D encoder, overfit to linguistic and answer-frequency shortcuts, and the proposed 3D-RDQA dataset helps expose and mitigate this problem.
V ote2cap-detr++: Decoupling localization and describing for end-to-end 3d dense captioning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(11):7331–7347, 2024
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs
3D scene-centric VLMs underutilize the 3D encoder, overfit to linguistic and answer-frequency shortcuts, and the proposed 3D-RDQA dataset helps expose and mitigate this problem.