Vineet, V.[Vibhav]
* 2008: CUDA cuts: Fast graph cuts on the GPU
* 2009: Solving Multilabel MRFs Using Incremental alpha-Expansion on the GPUs
* 2011: Human Instance Segmentation from Video using Detector-based Conditional Random Fields
* 2011: Struck: Structured Output Tracking with Kernels
* 2012: Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces
* 2012: Improved Initialization and Gaussian Mixture Pairwise Terms for Dense Random Fields with Mean-field Inference
* 2012: tiered move-making algorithm for general pairwise MRFs, A
* 2013: Efficient Salient Region Detection with Soft Image Abstraction
* 2014: Dense Semantic Image Segmentation with Objects and Attributes
* 2014: Distributed Non-convex ADMM-based inference in large-scale random fields
* 2014: Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces
* 2014: Visual Object Tracking VOT2014 Challenge Results, The
* 2015: Conditional Random Fields as Recurrent Neural Networks
* 2016: Dense Monocular Depth Estimation in Complex Dynamic Scenes
* 2016: Feature Space Optimization for Semantic Video Segmentation
* 2016: Playing for Data: Ground Truth from Computer Games
* 2016: Struck: Structured Output Tracking with Kernels
* 2019: Photorealistic Image Synthesis for Object Instance Detection
* 2020: Autosimulate: (quickly) Learning Synthetic Data Generation
* 2020: Depth Completion Using a View-constrained Deep Prior
* 2020: RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs
* 2022: Learning to Align Sequential Actions in the Wild
* 2022: MTFormer: Multi-task Learning via Transformer and Cross-Task Reasoning
* 2022: Neural-Sim: Learning to Generate Training Data with NeRF
* 2022: Robust Contrastive Learning against Noisy Views
* 2023: Efficiently Robustify Pre-Trained Models
* 2023: Exploring the Sim2Real Gap using Digital Twins
* 2023: Large-Scale Robustness Analysis of Video Action Recognition Models, A
* 2023: Scaling Novel Object Detection with Weakly Supervised Detection Transformers
Includes: Vineet, V.[Vibhav] Vineet, V.
29 for Vineet, V.
Vinel, A.[Antoine]
* 2011: Joint Optimization of Hidden Conditional Random Fields and Non Linear Feature Extraction
* 2013: Maximizing Edit Distance Accuracy with Hidden Conditional Random Fields
* 2013: On the Investigation of Cloud-Based Mobile Media Environments with Service-Populating and QoS-Aware Mechanisms
* 2013: Use of Automotive Radars in Video-Based Overtaking Assistance Applications, The
* 2018: Approach for Receiver-Side Awareness Control in Vehicular Ad Hoc Networks, An
* 2020: Internet Provisioning in VANETs: Performance Modeling of Drive-Thru Scenarios
* 2020: Toward Reliable and Scalable Internet of Vehicles: Performance Analysis and Resource Management
Includes: Vinel, A.[Antoine] Vinel, A.
7 for Vinel, A.
Vinent, O.D.[Orencio Duran]
* 2023: Application of CNN-Based Image Segmentation for Tracking Coastal Erosion and Post-Storm Recovery, The
Vines, B.W.[Bradley W.]
* 2003: Performance Gestures of Musicians: What Structural and Emotional Information Do They Convey?
Vinet, A.[Alain]
* 2019: Fibrillation Patterns Creep and Jump in a Detailed Three-Dimensional Model of the Human Atria
Vinet, L.
* 1989: Hierarchical Region Based Stereo Matching
Vineyard, C.M.[Craig M.]
* 2023: Research Challenges for Energy-Efficient Computing in Automated Vehicles