5 citations · 7 across the 8 of their papers we have counts for
8 papers · 1 filter
Harnessing Intrinsic Subject-Aware Attention for Controllable Multi-Subject Video Generation
Niange Yu, Ye Tian, Biaolong Chen +5
Multi-subject video generation faces two key challenges: uncontrollable fidelity strength and potential semantic drift. We address these by analyzing the internal mechanisms of Dif…
LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing
Jianzong Wu, Hao Lian, Jiongfan Yang +12
Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier field. Existing unified framewo…
Diffusion-APO: Trajectory-Aware Direct Preference Alignment for Video Diffusion Transformers
Jingyuan Zhu, Biaolong Chen, Le Zhang +3
Efficiently aligning large-scale video diffusion models with human intent requires a scalable and trajectory-aware pathway that bridges the inherent discrepancy between training no…
Denoising as Path Planning: Training-Free Acceleration of Diffusion Models with DPCache
Bowen Cui, Yuanbin Wang, Huajiang Xu +6
Diffusion models have demonstrated remarkable success in image and video generation, yet their practical deployment remains hindered by the substantial computational overhead of mu…
Does Hearing Help Seeing? Investigating Audio-Video Joint Denoising for Video Generation
Jianzong Wu, Hao Lian, Dachao Hao +5
Recent audio-video generative systems suggest that coupling modalities benefits not only audio-video synchrony but also the video modality itself. We pose a fundamental question: D…
ProFashion: Prototype-guided Fashion Video Generation with Multiple Reference Images
Xianghao Kong, Qiaosong Qi, Yuanbin Wang +3
Fashion video generation aims to synthesize temporally consistent videos from reference images of a designated character. Despite significant progress, existing diffusion-based met…
Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection
Luting Wang, Yi Liu, Penghui Du +5
Open-vocabulary object detection aims to provide object detectors trained on a fixed set of object categories with the generalizability to detect objects described by arbitrary tex…
Masked Contrastive Pre-Training for Efficient Video-Text Retrieval
Fangxun Shu, Biaolong Chen, Yue Liao +6
We present a simple yet effective end-to-end Video-language Pre-training (VidLP) framework, Masked Contrastive Video-language Pretraining (MAC), for video-text retrieval tasks. Our…