6 papers · 1 filter
Generative Recall, Dense Reranking: Learning Multi-View Semantic IDs for Efficient Text-to-Video Retrieval
Zecheng Zhao, Zhi Chen, Zi Huang +2
Text-to-Video Retrieval (TVR) is essential in video platforms. Dense retrieval with dual-modality encoders leads in accuracy, but its computation and storage scale poorly with corp…
Are Synthetic Videos Useful? A Benchmark for Retrieval-Centric Evaluation of Synthetic Videos
Zecheng Zhao, Selena Song, Tong Chen +3
Text-to-video (T2V) synthesis has advanced rapidly, yet current evaluation metrics primarily capture visual quality and temporal consistency, offering limited insight into how synt…
Continual Text-to-Video Retrieval with Frame Fusion and Task-Aware Routing
Zecheng Zhao, Zhi Chen, Zi Huang +2
Text-to-Video Retrieval (TVR) aims to retrieve relevant videos based on textual queries. However, as video content evolves continuously, adapting TVR systems to new data remains a…
SVIP: Semantically Contextualized Visual Patches for Zero-Shot Learning
Zhi Chen, Zecheng Zhao, Jingcai Guo +2
Zero-shot learning (ZSL) aims to recognize unseen classes without labeled training examples by leveraging class-level semantic descriptors such as attributes. A fundamental challen…
CF-PRNet: Coarse-to-Fine Prototype Refining Network for Point Cloud Completion and Reconstruction
Zhi Chen, Tianqi Wei, Zecheng Zhao +6
In modern agriculture, precise monitoring of plants and fruits is crucial for tasks such as high-throughput phenotyping and automated harvesting. This paper addresses the challenge…
FastEdit: Fast Text-Guided Single-Image Editing via Semantic-Aware Diffusion Fine-Tuning
Zhi Chen, Zecheng Zhao, Yadan Luo +1
Conventional Text-guided single-image editing approaches require a two-step process, including fine-tuning the target text embedding for over 1K iterations and the generative model…