SOTAVerified

Temporal Sequences

This task asks models to answer questions about which times certain events could have occurred.

Source: BIG-bench

Image source: BIG-bench

Papers

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Showing 26–50 of 200 papers

TitleStatusHype
A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in VideoCode1
CITRIS: Causal Identifiability from Temporal Intervened SequencesCode1
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold NetworksCode1
Predicting Human Scanpaths in Visual Question AnsweringCode1
TiMo: Spatiotemporal Foundation Model for Satellite Image Time SeriesCode1
Graph WaveNet for Deep Spatial-Temporal Graph ModelingCode1
Functional Map of the WorldCode1
Grid: Omni Visual GenerationCode1
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical MapsCode1
Learning future terrorist targets through temporal meta-graphsCode1
Leveraging Language Foundation Models for Human Mobility ForecastingCode1
A New Hybrid-parameter Recurrent Neural Networks for Online Handwritten Chinese Character Recognition—0
Computation with Sequences in a Model of the Brain—0
A generative model for surrogates of spatial-temporal wildfire nowcasting—0
Classifying Image Sequences of Astronomical Transients with Deep Neural Networks—0
An Efficient Volumetric Framework for Shape Tracking—0
FIBS: A Generic Framework for Classifying Interval-based Temporal Sequences—0
A Comprehensive Review of Few-shot Action Recognition—0
Anchor-Constrained Viterbi for Set-Supervised Action Segmentation—0
Exploiting Recurrent Neural Networks and Leap Motion Controller for Sign Language and Semaphoric Gesture Recognition—0
Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold—0
Biologically-Inspired Continual Learning of Human Motion Sequences—0
Easy attention: A simple attention mechanism for temporal predictions with transformers—0
Dynamic Time Warp Convolutional Networks—0
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution—0
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