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3D Object Manipulation in a Single Image using Generative Models
Ruisi Zhao, Zechuan Zhang, Zongxin Yang +1
Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling st…
Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data
Chao Liang, Linchao Zhu, Zongxin Yang +2
We focus on the challenging problem of learning an unbiased classifier from a large number of potentially relevant but noisily labeled web images given only a few clean labeled ima…
Prototype Learning for Micro-gesture Classification
Guoliang Chen, Fei Wang, Kun Li +5
In this paper, we briefly introduce the solution developed by our team, HFUT-VUT, for the track of Micro-gesture Classification in the MiGA challenge at IJCAI 2024. The task of mic…
Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion
Honglei Miao, Fan Ma, Ruijie Quan +2
Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text…
FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention
Yu Lu, Yuanzhi Liang, Linchao Zhu +1
Video diffusion models have made substantial progress in various video generation applications. However, training models for long video generation tasks require significant computa…
Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data
Tuo Feng, Wenguan Wang, Ruijie Quan +1
Current 3D self-supervised learning methods of 3D scenes face a data desert issue, resulting from the time-consuming and expensive collecting process of 3D scene data. Conversely,…