119 citations · 250 across the 20 of their papers we have counts for
20 papers
No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation
Xiangyang Zhu, Renrui Zhang, Bowei He +6
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'see…
Vision-Language Navigation with Embodied Intelligence: A Survey
Peng Gao, Peng Wang, Feng Gao +2
As a long-term vision in the field of artificial intelligence, the core goal of embodied intelligence is to improve the perception, understanding, and interaction capabilities of a…
Less is More: Towards Efficient Few-shot 3D Semantic Segmentation via Training-free Networks
Xiangyang Zhu, Renrui Zhang, Bowei He +4
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot semantic segmentation methods first pre-train the m…
Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
Siyuan Huang, Zhengkai Jiang, Hao Dong +3
Foundation models have made significant strides in various applications, including text-to-image generation, panoptic segmentation, and natural language processing. This paper pres…
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
Peng Gao, Jiaming Han, Renrui Zhang +9
How to efficiently transform large language models (LLMs) into instruction followers is recently a popular research direction, while training LLM for multi-modal reasoning remains…
Filter Pruning via Filters Similarity in Consecutive Layers
Xiaorui Wang, Jun Wang, Xin Tang +3
Filter pruning is widely adopted to compress and accelerate the Convolutional Neural Networks (CNNs), but most previous works ignore the relationship between filters and channels i…