27 citations · 94 across the 11 of their papers we have counts for
11 papers
Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee +2
Despite recent advances in Vision-Language Models (VLMs), they may over-rely on visual language priors existing in their training data rather than true visual reasoning. To investi…
View Selection for 3D Captioning via Diffusion Ranking
Tiange Luo, Justin Johnson, Honglak Lee
Scalable annotation approaches are crucial for constructing extensive 3D-text datasets, facilitating a broader range of applications. However, existing methods sometimes lead to th…
Scalable 3D Captioning with Pretrained Models
Tiange Luo, Chris Rockwell, Honglak Lee +1
We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects. This approach utilizes pretrained models from image captioning, image-text alignment, and…
Fine-grained Text Style Transfer with Diffusion-Based Language Models
Yiwei Lyu, Tiange Luo, Jiacheng Shi +2
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generat…
Multimodal Subtask Graph Generation from Instructional Videos
Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran +3
Real-world tasks consist of multiple inter-dependent subtasks (e.g., a dirty pan needs to be washed before it can be used for cooking). In this work, we aim to model the causal dep…
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program
Tiange Luo, Honglak Lee, Justin Johnson
3D shapes have complementary abstractions from low-level geometry to part-based hierarchies to languages, which convey different levels of information. This paper presents a unifie…