Search Results for author:
Found 6 papers, 4 papers with code
LatentArtiFusion: An Effective and Efficient Histological Artifacts Restoration Framework
In this paper, we propose a novel framework, LatentArtiFusion, which leverages the latent diffusion model (LDM) to reconstruct histological artifacts with high performance and computational efficiency.
ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling
Generative retrieval, which has demonstrated effectiveness in text-to-text retrieval, utilizes a sequence-to-sequence model to directly generate candidate identifiers based on natural language queries.
Prompt-Singer: Controllable Singing-Voice-Synthesis with Natural Language Prompt
Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and naturalness, yet they lack the capability to control the style attributes of the synthesized singing explicitly.
AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension
By revealing the limitations of existing LALMs through evaluation results, AIR-Bench can provide insights into the direction of future research.
DesignGPT: Multi-Agent Collaboration in Design
Generative AI faces many challenges when entering the product design workflow, such as interface usability and interaction patterns.
Diversity-Measurable Anomaly Detection
In this paper, to better handle the tradeoff problem, we propose Diversity-Measurable Anomaly Detection (DMAD) framework to enhance reconstruction diversity while avoid the undesired generalization on anomalies.
Ranked #1 on
Anomaly Detection
on UCSD Ped2
Anomaly Detection In Surveillance Videos
Defect Detection
+2
