13 citations · 14 across the 9 of their papers we have counts for
7 papers · 1 filter
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation
Mingfei Han, Liang Ma, Kamila Zhumakhanova +5
Vision-and-Language Navigation (VLN) suffers from the limited diversity and scale of training data, primarily constrained by the manual curation of existing simulators. To address…
Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes
Jianqi Chen, Panwen Hu, Xiaojun Chang +3
Recent advancements in human motion synthesis have focused on specific types of motions, such as human-scene interaction, locomotion or human-human interaction, however, there is a…
Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
Changlin Li, Jiawei Zhang, Sihao Lin +4
The rapid advancements in Large Vision Models (LVMs), such as Vision Transformers (ViTs) and diffusion models, have led to an increasing demand for computational resources, resulti…
Contrastive Learning with Counterfactual Explanations for Radiology Report Generation
Mingjie Li, Haokun Lin, Liang Qiu +4
Due to the common content of anatomy, radiology images with their corresponding reports exhibit high similarity. Such inherent data bias can predispose automatic report generation…
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label Classification
Gexin Huang, Chenfei Wu, Mingjie Li +6
Predicting genetic mutations from whole slide images is indispensable for cancer diagnosis. However, existing work training multiple binary classification models faces two challeng…
MLP Can Be A Good Transformer Learner
Sihao Lin, Pumeng Lyu, Dongrui Liu +4
Self-attention mechanism is the key of the Transformer but often criticized for its computation demands. Previous token pruning works motivate their methods from the view of comput…
DNA Family: Boosting Weight-Sharing NAS with Block-Wise Supervisions
Guangrun Wang, Changlin Li, Liuchun Yuan +5
Neural Architecture Search (NAS), aiming at automatically designing neural architectures by machines, has been considered a key step toward automatic machine learning. One notable…