Feichtenhofer, C.
* 2013: Perceptual Image Sharpness Metric Based on Local Edge Gradient Analysis, A
* 2013: Spacetime Forests with Complementary Features for Dynamic Scene Recognition
* 2013: Spatio-temporal Good Features to Track
* 2014: Bags of Spacetime Energies for Dynamic Scene Recognition
* 2015: Dynamically encoded actions based on spacetime saliency
* 2016: Convolutional Two-Stream Network Fusion for Video Action Recognition
* 2016: Dynamic Scene Recognition with Complementary Spatiotemporal Features
* 2017: Detect to Track and Track to Detect
* 2017: Spatiotemporal Multiplier Networks for Video Action Recognition
* 2017: Temporal Residual Networks for Dynamic Scene Recognition
* 2018: What have We Learned from Deep Representations for Action Recognition?
* 2019: 3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training
* 2019: Grounded Human-Object Interaction Hotspots From Video
* 2019: Long-Term Feature Banks for Detailed Video Understanding
* 2019: SlowFast Networks for Video Recognition
* 2020: Deep Insights into Convolutional Networks for Video Recognition
* 2020: Ego-Topo: Environment Affordances From Egocentric Video
* 2020: Modeling Human Motion with Quaternion-Based Neural Networks
* 2020: Multigrid Method for Efficiently Training Video Models, A
* 2020: X3D: Expanding Architectures for Efficient Video Recognition
* 2021: Large-Scale Study on Unsupervised Spatiotemporal Representation Learning, A
* 2021: Multiscale Vision Transformers
* 2021: Multiview Pseudo-Labeling for Semi-supervised Learning from Video
* 2022: ConvNet for the 2020s, A
* 2022: Ego4D: Around the World in 3,000 Hours of Egocentric Video
* 2022: Masked Feature Prediction for Self-Supervised Visual Pre-Training
* 2022: MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video Recognition
* 2022: MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
* 2022: Reversible Vision Transformers
* 2022: TrackFormer: Multi-Object Tracking with Transformers
* 2023: CiT: Curation in Training for Effective Vision-Language Data
* 2023: Diffusion Models as Masked Autoencoders
* 2023: effectiveness of MAE pre-pretraining for billion-scale pretraining, The
* 2023: Multiview Compressive Coding for 3D Reconstruction
* 2023: On the Benefits of 3D Pose and Tracking for Human Action Recognition
* 2023: Scaling Language-Image Pre-Training via Masking
Includes: Feichtenhofer, C. Feichtenhofer, C.[Christoph]
36 for Feichtenhofer, C.
Feichtinger, C.[Christian]
* 2011: Geometric Multigrid Solver on Tsubame 2.0, A
Feichtinger, H.G.
* 1993: Fast iterative reconstruction of band-limited images from non-uniform sampling values
* 1996: Gabor Systems with Good TF-Localization and Applications to Image Processing
* 1997: On a Complementary Condition to Derivation of Discrete Gabor Expansions
* 2004: Approximation of Matrices by Gabor Multipliers
Includes: Feichtinger, H.G. Feichtinger, H.G.[Hans G.]
Feick, R.[Rob]
* 2004: Predicting Forest Age Classes from High Spatial Resolution Remotely Sensed Imagery Using Voronoi Polygon Aggregation
* 2010: Exploring rooftop photovoltaic cell feasibility through web-GIS
* 2010: Geovisualisation methods for exploring urban heat island effects
* 2016: Understanding Public Opinions from Geosocial Media
* 2020: Spatial-Comprehensiveness (S-COM) Index: Identifying Optimal Spatial Extents in Volunteered Geographic Information Point Datasets, The
* 2021: CWDAT: An Open-Source Tool for the Visualization and Analysis of Community-Generated Water Quality Data
Includes: Feick, R.[Rob] Feick, R.[Robert]