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Found 8 papers, 5 papers with code
Data-Prep-Kit: getting your data ready for LLM application development
We believe DPK is a valuable contribution to the AI community to easily prepare data to enhance the performance of their LLM models or to fine-tune models with Retrieval-Augmented Generation (RAG).
HASSOD: Hierarchical Adaptive Self-Supervised Object Detection
The human visual perception system demonstrates exceptional capabilities in learning without explicit supervision and understanding the part-to-whole composition of objects.
Contrastive Mean Teacher for Domain Adaptive Object Detectors
Object detectors often suffer from the domain gap between training (source domain) and real-world applications (target domain).
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning
Predictions made by deep learning models are prone to data perturbations, adversarial attacks, and out-of-distribution inputs.
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Further, we propose a tri-modal model that jointly processes raw audio, video, and text captions from videos to learn a multi-modal semantic embedding space useful for text-video retrieval.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey
Affective computing (AC) of these data can help to understand human behaviors and enable wide applications.
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection
Fine-grained action detection is an important task with numerous applications in robotics and human-computer interaction.
Automatic Curation of Golf Highlights using Multimodal Excitement Features
The production of sports highlight packages summarizing a game's most exciting moments is an essential task for broadcast media.
