5 papers · 1 filter
SAB3R: Semantic-Augmented Backbone in 3D Reconstruction
Xuweiyi Chen, Tian Xia, Sihan Xu +3
We introduce a new task, Map and Locate, which unifies the traditionally distinct objectives of open-vocabulary segmentation - detecting and segmenting object instances based on na…
3D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination
Jianing Yang, Xuweiyi Chen, Nikhil Madaan +4
The integration of language and 3D perception is crucial for embodied agents and robots that comprehend and interact with the physical world. While large language models (LLMs) hav…
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Jianing Yang, Alexander Sax, Kevin J. Liang +6
Multi-view 3D reconstruction remains a core challenge in computer vision, particularly in applications requiring accurate and scalable representations across diverse perspectives.…
Multi-Object Hallucination in Vision-Language Models
Xuweiyi Chen, Ziqiao Ma, Xuejun Zhang +5
Large vision language models (LVLMs) often suffer from object hallucination, producing objects not present in the given images. While current benchmarks for object hallucination pr…
GROUNDHOG: Grounding Large Language Models to Holistic Segmentation
Yichi Zhang, Ziqiao Ma, Xiaofeng Gao +3
Most multimodal large language models (MLLMs) learn language-to-object grounding through causal language modeling where grounded objects are captured by bounding boxes as sequences…