STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing | Paper Citation Record

Observation e5777d03-5ff1-443a-a5f0-87f279d05695 · outbound

This paper cites Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving

Reference 1

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Observation 6d2589de-e0d0-4049-8370-2db9103bb5fd · outbound

This paper cites Efficient prediction of human motion for real-time robotics applica- tions with physics-inspired neural networks.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Efficient prediction of human motion for real-time robotics applica- tions with physics-inspired neural networks

Reference 2

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Observation a9e73dc2-6be2-4a4f-9ea8-ffcd7077f554 · outbound

This paper cites Anticipating many futures: Online human motion predic- tion and generation for human-robot interaction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Anticipating many futures: Online human motion predic- tion and generation for human-robot interaction

Reference 3

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This paper cites Mau: A motion- aware unit for video prediction and beyond.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Mau: A motion- aware unit for video prediction and beyond

Reference 4

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This paper cites CycleMLP: A MLP-like Architecture for Dense Prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing CycleMLP: A MLP-like Architecture for Dense Prediction

Reference 5

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This paper cites Spatio-temporal image representation and deep- learning-based decision framework for automated vehicles.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Spatio-temporal image representation and deep- learning-based decision framework for automated vehicles

Reference 6

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This paper cites Inductive Bias of Deep Convolutional Networks through Pooling Geometry.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Inductive Bias of Deep Convolutional Networks through Pooling Geometry

Reference 7

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This paper cites Pedestrian detection: A benchmark.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Pedestrian detection: A benchmark

Reference 8

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Observation c20f7826-48b0-4f95-b329-b770ced21ef2 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Unresolved cited work

Reference 10

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This paper cites Simvp: Simpler yet better video prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Simvp: Simpler yet better video prediction

Reference 11

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Observation 2764772a-c992-46ca-9dfc-d2ebfce0fc52 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 12

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This paper cites Deep Learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Deep Learning

Reference 13

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This paper cites Disentangling physi- cal dynamics from unknown factors for unsupervised video prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Disentangling physi- cal dynamics from unknown factors for unsupervised video prediction

Reference 14

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This paper cites Classifying pedestrian actions in advance using predicted video of urban driving scenes.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Classifying pedestrian actions in advance using predicted video of urban driving scenes

Reference 15

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This paper cites Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification

Reference 16

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This paper cites A dynamic multi-scale voxel flow network for video prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing A dynamic multi-scale voxel flow network for video prediction

Reference 17

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Observation 0ad150f8-76c1-4256-bf94-cb6003ea3c92 · outbound

This paper cites Learning robot activities from first-person human videos using convolutional future regression.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Learning robot activities from first-person human videos using convolutional future regression

Reference 18

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This paper cites More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Reference 19

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This paper cites A convnet for the 2020s.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing A convnet for the 2020s

Reference 20

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This paper cites Video frame synthesis using deep voxel flow.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Video frame synthesis using deep voxel flow

Reference 21

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Observation 82649d70-2b67-47e1-a124-48a8d8811d83 · outbound

This paper cites Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

Reference 22

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This paper cites Predicting fu- ture occupancy grids in dynamic environment with spatio- temporal learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predicting fu- ture occupancy grids in dynamic environment with spatio- temporal learning

Reference 23

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This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing U- net: Convolutional networks for biomedical image segmen- tation

Reference 24

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This paper cites Rousseeuw.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Rousseeuw

Reference 25

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This paper cites Recog- nizing human actions: a local svm approach.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Recog- nizing human actions: a local svm approach

Reference 26

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Observation f4b0a008-30d1-4184-9d92-a3ae74ed0269 · outbound

This paper cites Implicit Stacked Autoregressive Model for Video Prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Implicit Stacked Autoregressive Model for Video Prediction

Reference 27

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This paper cites Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Reference 28

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This paper cites Convolutional lstm network: A machine learning approach for precipitation nowcasting.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Convolutional lstm network: A machine learning approach for precipitation nowcasting

Reference 29

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This paper cites Unsupervised learning of video representations using lstms.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Unsupervised learning of video representations using lstms

Reference 30

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This paper cites Sequence to sequence learning with neural networks.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Sequence to sequence learning with neural networks

Reference 31

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This paper cites Going deeper with convolutions.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Going deeper with convolutions

Reference 32

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This paper cites Temporal attention unit: To- wards efficient spatiotemporal predictive learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Temporal attention unit: To- wards efficient spatiotemporal predictive learning

Reference 33

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Observation 520de40a-a81d-411d-a512-4db84a6e8289 · outbound

This paper cites OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Reference 34

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This paper cites Mlp-mixer: An all-mlp architecture for vision.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Mlp-mixer: An all-mlp architecture for vision

Reference 35

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This paper cites Resmlp: Feedforward networks for image classification with data-efficient training.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Resmlp: Feedforward networks for image classification with data-efficient training

Reference 36

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This paper cites Patches Are All You Need?.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Patches Are All You Need?

Reference 37

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This paper cites Attention is all you need.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Attention is all you need

Reference 38

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This paper cites Decomposing Motion and Content for Natural Video Sequence Prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Decomposing Motion and Content for Natural Video Sequence Prediction

Reference 39

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Observation 0f8393fe-66e5-44b4-829c-4266eaceb0a1 · outbound

This paper cites Mcvd-masked conditional video diffusion for prediction, generation, and interpolation.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Mcvd-masked conditional video diffusion for prediction, generation, and interpolation

Reference 40

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Observation c8835ff8-8246-4f36-8664-f65e3fb46588 · outbound

This paper cites Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning

Reference 41

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Observation ec406a26-d675-4a55-a465-2e6b5ff2c5fe · outbound

This paper cites Eidetic 3d lstm: A model for video prediction and beyond.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Eidetic 3d lstm: A model for video prediction and beyond

Reference 42

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This paper cites Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms

Reference 43

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This paper cites Predrnn: A recurrent neural network for spatiotemporal predictive learn- ing.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predrnn: A recurrent neural network for spatiotemporal predictive learn- ing

Reference 44

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Observation 8bc093b9-fee4-4230-9f56-33da4aa15339 · outbound

This paper cites Memory in memory: A predictive neural network for learning higher-order non- stationarity from spatiotemporal dynamics.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Memory in memory: A predictive neural network for learning higher-order non- stationarity from spatiotemporal dynamics

Reference 45

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Observation dedf46c7-7b0d-4fa4-8d39-9f790af1bd2b · outbound

This paper cites Sample-efficient reinforcement learning via conservative model-based actor-critic.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Sample-efficient reinforcement learning via conservative model-based actor-critic

Reference 46

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Observation c4d95904-2d0a-4fe7-baf2-deb7c58ba17f · outbound

This paper cites Theoretical analysis of the induc- tive biases in deep convolutional networks.Advances in Neu- ral Information Processing Systems, 36, 2024.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Theoretical analysis of the induc- tive biases in deep convolutional networks.Advances in Neu- ral Information Processing Systems, 36, 2024

Reference 47

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This paper cites Sample efficient deep reinforcement learning for dialogue systems with large action spaces.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Sample efficient deep reinforcement learning for dialogue systems with large action spaces

Reference 48

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Observation 812dfe92-d89b-4203-834f-2ab7a377edfd · outbound

This paper cites PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

Reference 49

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Observation 3e1e0875-42d6-4c05-9cdd-57a28977a129 · outbound

This paper cites Predcnn: Predictive learning with cascade convo- lutions.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predcnn: Predictive learning with cascade convo- lutions

Reference 50

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Observation b57a6bbb-7f66-410a-adea-5d321787510e · outbound

This paper cites Vptr: Efficient transformers for video prediction.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Vptr: Efficient transformers for video prediction

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T19:55:10.135815Z

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Unavailable: canonical work link unavailable.

Observation fcada6cc-c360-4ba9-b884-e11d7d8f2726 · outbound

This paper cites Crevnet: Conditionally reversible video prediction, 2019.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Crevnet: Conditionally reversible video prediction, 2019

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.385153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fc2a83ea-2d41-4fbd-afdf-da3979ab0e83 · outbound

This paper cites Efficient and information-preserving future frame prediction and beyond.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Efficient and information-preserving future frame prediction and beyond

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.374895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fee79c12-bdc3-4ee3-a631-a6f8027b93ab · outbound

This paper cites Predicting citywide crowd flows using deep spatio-temporal residual networks.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Predicting citywide crowd flows using deep spatio-temporal residual networks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.363158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eea4b4fd-078d-434c-a64e-02952c8556b0 · outbound

This paper cites Pose-forecasting aided human video prediction with graph convolutional networks.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Pose-forecasting aided human video prediction with graph convolutional networks

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.352472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 509ec157-59dc-44d0-86f7-d84a13688fe3 · outbound

This paper cites • Repeated STLMixer The parameter count from our proposed STLMixer architecture is O de · (d2 + d · k2 T1 + d · k2 T2 ).

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing • Repeated STLMixer The parameter count from our proposed STLMixer architecture is O de · (d2 + d · k2 T1 + d · k2 T2 )

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.341162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 54079ed0-07ea-4e2a-809c-6eaaa7ecc0fe · outbound

This paper cites Similarly k2 T1 ≪ d and k2 T2 ≪ d.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing Similarly k2 T1 ≪ d and k2 T2 ≪ d

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.330379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b428b63e-bcd1-4d3d-9ca7-bc7a65cd4388 · outbound

This paper cites dis- persion.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing dis- persion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.319729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1a87e3e7-f773-49bf-8522-5f2e505db882 · outbound

This paper cites IEEE, 2004.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing IEEE, 2004

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:55:10.597816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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