7 citations · 15 across the 6 of their papers we have counts for
16 papers · 1 filter
Learning Visual Grounding from Generative Vision and Language Model
Shijie Wang, Dahun Kim, Ali Taalimi +2
Visual grounding tasks aim to localize image regions based on natural language references. In this work, we explore whether generative VLMs predominantly trained on image-text data…
3D Open-Vocabulary Panoptic Segmentation with 2D-3D Vision-Language Distillation
Zihao Xiao, Longlong Jing, Shangxuan Wu +9
3D panoptic segmentation is a challenging perception task, especially in autonomous driving. It aims to predict both semantic and instance annotations for 3D points in a scene. Alt…
Region-centric Image-Language Pretraining for Open-Vocabulary Detection
Dahun Kim, Anelia Angelova, Weicheng Kuo
We present a new open-vocabulary detection approach based on region-centric image-language pretraining to bridge the gap between image-level pretraining and open-vocabulary object…
Contrastive Feature Masking Open-Vocabulary Vision Transformer
Dahun Kim, Anelia Angelova, Weicheng Kuo
We present Contrastive Feature Masking Vision Transformer (CFM-ViT) - an image-text pretraining methodology that achieves simultaneous learning of image- and region-level represent…
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
Xiuye Gu, Yin Cui, Jonathan Huang +8
Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We u…
Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers
Dahun Kim, Anelia Angelova, Weicheng Kuo
We present Region-aware Open-vocabulary Vision Transformers (RO-ViT) - a contrastive image-text pretraining recipe to bridge the gap between image-level pretraining and open-vocabu…