13 citations · 39 across the 11 of their papers we have counts for
11 papers
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale
Joya Chen, Ziyun Zeng, Yiqi Lin +3
Recent video large language models (Video LLMs) often depend on costly human annotations or proprietary model APIs (e.g., GPT-4o) to produce training data, which limits their train…
TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation
Alex Jinpeng Wang, Dongxing Mao, Jiawei Zhang +9
Text-conditioned image generation has gained significant attention in recent years and are processing increasingly longer and comprehensive text prompt. In everyday life, dense and…
Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning
Alex Jinpeng Wang, Linjie Li, Yiqi Lin +3
Training models with longer in-context lengths is a significant challenge for multimodal model due to substantial GPU memory and computational costs. This exploratory study does no…
Parrot Captions Teach CLIP to Spot Text
Yiqi Lin, Conghui He, Alex Jinpeng Wang +3
Despite CLIP being the foundation model in numerous vision-language applications, the CLIP suffers from a severe text spotting bias. Such bias causes CLIP models to `Parrot' the vi…
Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback
Yiqi Lin, Hao Wu, Ruichen Wang +4
Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within…
CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout
Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang +4
Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusi…
Priors in Deep Image Restoration and Enhancement: A Survey
Yunfan Lu, Yiqi Lin, Hao Wu +4
Image restoration and enhancement is a process of improving the image quality by removing degradations, such as noise, blur, and resolution degradation. Deep learning (DL) has rece…
Exploring the Interactive Guidance for Unified and Effective Image Matting
Dinghao Yang, Bin Wang, Weijia Li +2
Recent image matting studies are developing towards proposing trimap-free or interactive methods for complete complex image matting tasks. Although avoiding the extensive labors of…
Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning
Jinpeng Wang, Yuting Gao, Ke Li +7
Self-supervised learning has shown great potentials in improving the video representation ability of deep neural networks by getting supervision from the data itself. However, some…
Self-supervised Temporal Discriminative Learning for Video Representation Learning
Jinpeng Wang, Yiqi Lin, Andy J. Ma +1
Temporal cues in videos provide important information for recognizing actions accurately. However, temporal-discriminative features can hardly be extracted without using an annotat…
Self-supervised learning using consistency regularization of spatio-temporal data augmentation for action recognition
Jinpeng Wang, Yiqi Lin, Andy J. Ma
Self-supervised learning has shown great potentials in improving the deep learning model in an unsupervised manner by constructing surrogate supervision signals directly from the u…