9 citations · 47 across the 11 of their papers we have counts for
11 papers
Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation
Lingting Zhu, Xian Liu, Xuanyu Liu +3
Animating virtual avatars to make co-speech gestures facilitates various applications in human-machine interaction. The existing methods mainly rely on generative adversarial netwo…
Motion-inductive Self-supervised Object Discovery in Videos
Shuangrui Ding, Weidi Xie, Yabo Chen +4
In this paper, we consider the task of unsupervised object discovery in videos. Previous works have shown promising results via processing optical flows to segment objects. However…
Static and Dynamic Concepts for Self-supervised Video Representation Learning
Rui Qian, Shuangrui Ding, Xian Liu +1
In this paper, we propose a novel learning scheme for self-supervised video representation learning. Motivated by how humans understand videos, we propose to first learn general vi…
Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset
Grant Van Horn, Rui Qian, Kimberly Wilber +3
We present a new benchmark dataset, Sapsucker Woods 60 (SSW60), for advancing research on audiovisual fine-grained categorization. While our community has made great strides in fin…
Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models
Rui Qian, Yeqing Li, Zheng Xu +3
Utilizing vision and language models (VLMs) pre-trained on large-scale image-text pairs is becoming a promising paradigm for open-vocabulary visual recognition. In this work, we ex…
Controllable Augmentations for Video Representation Learning
Rui Qian, Weiyao Lin, John See +1
This paper focuses on self-supervised video representation learning. Most existing approaches follow the contrastive learning pipeline to construct positive and negative pairs by s…
Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Generation
Xian Liu, Qianyi Wu, Hang Zhou +7
Generating speech-consistent body and gesture movements is a long-standing problem in virtual avatar creation. Previous studies often synthesize pose movement in a holistic manner,…
Visual Sound Localization in the Wild by Cross-Modal Interference Erasing
Xian Liu, Rui Qian, Hang Zhou +5
The task of audio-visual sound source localization has been well studied under constrained scenes, where the audio recordings are clean. However, in real-world scenarios, audios ar…
Class-aware Sounding Objects Localization via Audiovisual Correspondence
Di Hu, Yake Wei, Rui Qian +3
Audiovisual scenes are pervasive in our daily life. It is commonplace for humans to discriminatively localize different sounding objects but quite challenging for machines to achie…
Exploring Temporal Granularity in Self-Supervised Video Representation Learning
Rui Qian, Yeqing Li, Liangzhe Yuan +7
This work presents a self-supervised learning framework named TeG to explore Temporal Granularity in learning video representations. In TeG, we sample a long clip from a video and…
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas +5
Building instance segmentation models that are data-efficient and can handle rare object categories is an important challenge in computer vision. Leveraging data augmentations is a…