7 papers
Extending a Large View Synthesis Model for Multi-view Panoptic Segmentation
Kwonyoung Ryu, In-Jae Lee, Jonghyun Jin +3
Large view synthesis models synthesize novel views through cross-view attention without explicit 3D representations, and recent studies have shown that they learn accurate spatial…
Relation-Centric Open-Vocabulary 3D Gaussian Segmentation
Eunsung Cha, Hyunjoon Lee, Jaesik Park
Open-vocabulary 3D Gaussian segmentation is challenging because it requires language understanding for diverse queries and accurate separation of Gaussians along object boundaries.…
Why Far Looks Up: Probing Spatial Representation in Vision-Language Models
Cheolhong Min, Jaeyun Jung, Daeun Lee +5
Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D understanding or reliance on st…
Taking Shortcuts for Categorical VQA Using Super Neurons
Pierre Musacchio, Jaeyi Jeong, Dahun Kim +1
Sparse Attention Vectors (SAVs) have emerged as an excellent training-free alternative to supervised finetuning or low-rank adaptation to improve the performance of Vision Language…
OpenBox: Annotate Any Bounding Boxes in 3D
In-Jae Lee, Mungyeom Kim, Kwonyoung Ryu +2
Unsupervised and open-vocabulary 3D object detection has recently gained attention, particularly in autonomous driving, where reducing annotation costs and recognizing unseen objec…
Holistic Order Prediction in Natural Scenes
Pierre Musacchio, Hyunmin Lee, Jaesik Park
Even in controlled settings, understanding instance-wise geometries is a challenging task for a wide range of visual models. Although specialized systems exist, modern arts rely on…