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Found 11 papers, 2 papers with code
Distilling Vision-Language Models on Millions of Videos
Our best model outperforms state-of-the-art methods on MSR-VTT zero-shot text-to-video retrieval by 6%.
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
To be commensurate with this capacity, in addition to the real data used for pre-training, we also generated and leveraged synthetic ophthalmic imaging data.
RFDforFin: Robust Deep Forgery Detection for GAN-generated Fingerprint Images
In this paper, we propose the first deep forgery detection approach for fingerprint images, which combines unique ridge features of fingerprint and generation artifacts of the GAN-generated images, to the best of our knowledge.
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities
Machine learning (ML) is now commonplace, powering data-driven applications in various organizations.
Robust 2D/3D Vehicle Parsing in CVIS
We combine these novel algorithms and datasets to develop a robust approach for 2D/3D vehicle parsing for CVIS.
Robust 2D/3D Vehicle Parsing in Arbitrary Camera Views for CVIS
We combine these novel algorithms and datasets to develop a robust approach for 2D/3D vehicle parsing for CVIS.
Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation
For autonomous driving, the dynamics and states of vehicle parts such as doors, the trunk, and the bonnet can provide meaningful semantic information and interaction states, which are essential to ensuring the safety of the self-driving vehicle.
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving
We present a novel approach to detect, segment, and reconstruct complete textured 3D models of vehicles from a single image for autonomous driving.
ModelHub: Towards Unified Data and Lifecycle Management for Deep Learning
Deep learning modeling lifecycle generates a rich set of data artifacts, such as learned parameters and training logs, and comprises of several frequently conducted tasks, e. g., to understand the model behaviors and to try out new models.
ProvDB: A System for Lifecycle Management of Collaborative Analysis Workflows
As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier to keep track of the analyses being performed and datasets being generated, and to enable introspection of the workflows.
Databases
A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization
In modern data science problems, techniques for extracting value from big data require performing large-scale optimization over heterogenous, irregularly structured data.
