4 citations · 7 across the 7 of their papers we have counts for
7 papers
LoRA in LoRA: Towards Parameter-Efficient Architecture Expansion for Continual Visual Instruction Tuning
Chang Che, Ziqi Wang, Pengwan Yang +3
Continual Visual Instruction Tuning (CVIT) enables Multimodal Large Language Models (MLLMs) to incrementally learn new tasks over time. However, this process is challenged by catas…
Segment Any 3D-Part in a Scene from a Sentence
Hongyu Wu, Pengwan Yang, Yuki M. Asano +1
This paper aims to achieve the segmentation of any 3D part in a scene based on natural language descriptions, extending beyond traditional object-level 3D scene understanding and a…
Self-Ordering Point Clouds
Pengwan Yang, Cees G. M. Snoek, Yuki M. Asano
In this paper we address the task of finding representative subsets of points in a 3D point cloud by means of a point-wise ordering. Only a few works have tried to address this cha…
Less than Few: Self-Shot Video Instance Segmentation
Pengwan Yang, Yuki M. Asano, Pascal Mettes +1
The goal of this paper is to bypass the need for labelled examples in few-shot video understanding at run time. While proven effective, in many practical video settings even labell…
Few-Shot Transformation of Common Actions into Time and Space
Pengwan Yang, Pascal Mettes, Cees G. M. Snoek
This paper introduces the task of few-shot common action localization in time and space. Given a few trimmed support videos containing the same but unknown action, we strive for sp…
Localizing the Common Action Among a Few Videos
Pengwan Yang, Vincent Tao Hu, Pascal Mettes +1
This paper strives to localize the temporal extent of an action in a long untrimmed video. Where existing work leverages many examples with their start, their ending, and/or the cl…
PointMixup: Augmentation for Point Clouds
Yunlu Chen, Vincent Tao Hu, Efstratios Gavves +4
This paper introduces data augmentation for point clouds by interpolation between examples. Data augmentation by interpolation has shown to be a simple and effective approach in th…