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Found 8 papers, 4 papers with code
STT: Stateful Tracking with Transformers for Autonomous Driving
In this paper, we propose STT, a Stateful Tracking model built with Transformers, that can consistently track objects in the scenes while also predicting their states accurately.
Joint Forecasting of Panoptic Segmentations with Difference Attention
For this, panoptic segmentations have been studied as a compelling representation in recent work.
Panoptic Segmentation Forecasting
Following this decomposition, we introduce panoptic segmentation forecasting.
Dynamic Neural Relational Inference
Understanding interactions between entities, e. g., joints of the human body, team sports players, etc., is crucial for tasks like forecasting.
Graph Structured Prediction Energy Networks
For joint inference over multiple variables, a variety of structured prediction techniques have been developed to model correlations among variables and thereby improve predictions.
Unsupervised Discovery of Dynamic Neural Circuits
What can we learn about the functional organization of cortical microcircuits from large-scale recordings of neural activity?
Deep Structured Prediction with Nonlinear Output Transformations
Deep structured models are widely used for tasks like semantic segmentation, where explicit correlations between variables provide important prior information which generally helps to reduce the data needs of deep nets.
Towards Problem Solving Agents that Communicate and Learn
Agents that communicate back and forth with humans to help them execute non-linguistic tasks are a long sought goal of AI.
