SOTAVerified

Video Prediction

Script for Amee Marketing & Trading Company Short Video
(Duration: 45-60 seconds)


Opening Scene (0:00-0:05):

  • Visual: Close-up of fresh organic grains spilling gently into a wooden bowl. Sunlight filters through lush green fields.
  • Text Overlay: "Nourishing Lives, Naturally."
  • Music: Uplifting acoustic melody with a traditional touch.

Scene 1: Organic & Natural Offerings (0:05-0:15):

  • Visual: Rapid montage of vibrant vegetables, ripe fruits, aromatic spices, Ayurvedic herbs, and fresh dairy products.
  • Voiceover: "At Amee Marketing & Trading, we bring you the purest Vedic organic foods—grains, spices, herbs, and dairy—straight from nature’s bounty."

Scene 2: Engineering & Innovation (0:15-0:25):

  • Visual: Split-screen transition:
    • Left: Engineers working on agriculture machinery and water treatment systems.
    • Right: Automation controls, aquaculture systems, and textile equipment in action.
  • Voiceover: "Pioneering sustainable solutions—agriculture engineering, water and wastewater treatment, automation, and industrial innovations."

Scene 3: Waste & Resource Management (0:25-0:35):

  • Visual: Waste management systems transforming waste into resources, followed by Roadtech equipment paving roads.
  • Text Overlay: "Building a greener future."
  • Voiceover: "From waste management to infrastructure, we engineer tomorrow’s world today."

Scene 4: Services & Global Reach (0:35-0:45):

  • Visual: Factory assembly line, team meeting, and global map with location pins.
  • Voiceover: "As manufacturers, traders, and suppliers, we bridge quality and trust worldwide."

Closing Scene (0:45-0:55):

  • Visual: Amee logo fades in over a backdrop of their factory. Contact details appear.
  • Text Overlay: "Connect with Us!"
    • Phone: +91-8300874712
    • Website: www.ameemarketingtredingcompany.in
    • Location: Home & Factory (add brief map graphic).
  • Voiceover: "Your partner in purity and progress. Contact Amee today!"

End Frame (0:55-1:00):

  • Visual: Sunrise over fields with the tagline: "Amee Marketing & Trading – Where Tradition Meets Technology."

Production Notes:

  • Music: Blend traditional Indian instruments with modern beats for cross-sector appeal.
  • Color Palette: Earthy tones (greens, browns) for organic segments; metallic blues/greys for tech sections.
  • Pacing: Quick cuts for energy, but hold 2-3 seconds on contact details.

Perfect for social media ads or website headers! 🌱🚀

Gif credit: MAGVIT

Source: Photo-Realistic Video Prediction on Natural Videos of Largely Changing Frames

Papers

Showing 101–150 of 394 papers

TitleStatusHype
Continual Predictive Learning from VideosCode1
Video Prediction by Efficient TransformersCode1
Deep learning for satellite image forecasting of vegetation greennessCode1
Video Prediction via Example GuidanceCode1
Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video SynthesisCode1
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying MotionsCode1
Motion Segmentation using Frequency Domain Transformer NetworksCode1
3D-CSL: self-supervised 3D context similarity learning for Near-Duplicate Video RetrievalCode1
Convolutional LSTM Network: A Machine Learning Approach for Precipitation NowcastingCode1
Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMsCode1
Implicit Stacked Autoregressive Model for Video PredictionCode1
A Control-Centric Benchmark for Video PredictionCode1
Convolutional Tensor-Train LSTM for Spatio-temporal LearningCode1
DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent ParticlesCode1
MAU: A Motion-Aware Unit for Video Prediction and BeyondCode1
MIMO Is All You Need : A Strong Multi-In-Multi-Out Baseline for Video PredictionCode1
Multi-view Action Recognition using Cross-view Video PredictionCode1
GATSBI: Generative Agent-centric Spatio-temporal Object InteractionCode1
MS-RNN: A Flexible Multi-Scale Framework for Spatiotemporal Predictive LearningCode1
Unsupervised Image Representation Learning with Deep Latent ParticlesCode1
Advection Augmented Convolutional Neural NetworksCode1
Data-Driven Uncertainty-Aware Forecasting of Sea Ice Conditions in the Gulf of Ob Based on Satellite Radar Imagery—0
Fourier-based Video Prediction through Relational Object Motion—0
Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction—0
FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation—0
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices—0
Flexible Spatio-Temporal Networks for Video Prediction—0
Long-Term Human Video Generation of Multiple Futures Using Poses—0
FitVid: High-Capacity Pixel-Level Video Prediction—0
Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns—0
CrevNet: Conditionally Reversible Video Prediction—0
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space—0
A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches—0
Cubic LSTMs for Video Prediction—0
Long History Short-Term Memory for Long-Term Video Prediction—0
Face Translation between Images and Videos using Identity-aware CycleGAN—0
ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction—0
Convolutional Tensor-Train LSTM for Long-Term Video Prediction—0
Long-horizon video prediction using a dynamic latent hierarchy—0
Masked Generative Priors Improve World Models Sequence Modelling Capabilities—0
Experience-Embedded Visual Foresight—0
EVA: An Embodied World Model for Future Video Anticipation—0
Controllable Video Generation With Sparse Trajectories—0
Learning to Identify Physical Parameters from Video Using Differentiable Physics—0
Continuous Video Process: Modeling Videos as Continuous Multi-Dimensional Processes for Video Prediction—0
Enhancing Traffic Scene Predictions with Generative Adversarial Networks—0
Enhanced Spatiotemporal Prediction Using Physical-guided And Frequency-enhanced Recurrent Neural Networks—0
A Review on Deep Learning Techniques for Video Prediction—0
Learning what you can do before doing anything—0
End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation—0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Struct-VRNN (from Grid-keypoints)FVD395—Unverified
2SV2P time-invariant (from Grid-keypoints)FVD253.5—Unverified
3SV2P time-invariant (from Grid-keypoints)FVD209.5—Unverified
4SAVP (from Grid-keypoints)FVD183.7—Unverified
5SVG-LP (from Grid-keypoints)FVD157.9—Unverified
6SAVP-VAE (from Grid-keypoints)FVD145.7—Unverified
7Grid-keypointsFVD144.2—Unverified
8SVG-LP (from SRVP)Cond10—Unverified
9SLAMPCond10—Unverified
10SAVP (from SRVP)Cond10—Unverified
#ModelMetricClaimedVerifiedStatus
1ConvLSTMMSE103.3—Unverified
2PredRNNMSE56.8—Unverified
3MIMMSE52—Unverified
4PredRNN-V2MSE48.4—Unverified
5Causal LSTMMSE46.5—Unverified
6MIM*MSE44.2—Unverified
7SA-ConvLSTMMSE43.9—Unverified
8LMCMSE41.5—Unverified
9E3D-LSTMMSE41.3—Unverified
10CrevNet+ConvLSTMMSE38.5—Unverified
#ModelMetricClaimedVerifiedStatus
1LVTFVD224.73—Unverified
2OmniTokenizer-ARFVD32.9—Unverified
3RaMViDFVD16.46—Unverified
4RIN (400 steps)FVD11.5—Unverified
5RIN (1000 steps)FVD10.8—Unverified
6LARPFVD5.1—Unverified
7DVD-GAN-FPCond5—Unverified
8MAGVIT (-L-FP)Cond5—Unverified
9MAGVIT (-B-FP)Cond5—Unverified
10TriVD-GAN-FPCond5—Unverified
#ModelMetricClaimedVerifiedStatus
1IAM4VPSSIM0.94—Unverified
2SwinLSTMSSIM0.91—Unverified
3FFINetSSIM0.91—Unverified
4SimVPSSIM0.9—Unverified
5PhyDNetSSIM0.9—Unverified
6E3D-LSTMSSIM0.87—Unverified
7MIMSSIM0.79—Unverified
8PredRNNSSIM0.78—Unverified
9FRNNSSIM0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1SVG (from Hier-VRNN)FVD1,300.26—Unverified
2Hier-VRNNFVD567.51—Unverified
3SLAMPCond.10—Unverified
4SRVPCond.10—Unverified
5GHVAEsCond.2—Unverified
#ModelMetricClaimedVerifiedStatus
1SVG-DetLPIPS0.07—Unverified
2SVG-LPLPIPS0.07—Unverified
3PhyDNetLPIPS0.05—Unverified
4PredRNN++LPIPS0.05—Unverified
5MSPredLPIPS0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1DVGFVD120.03—Unverified
2DVD-GAN-FPFVD109.8—Unverified
3PhenakiFVD97—Unverified
4MMVGFVD85.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ODE2VAETest Error10.06—Unverified
2ODE2VAE-KLTest Error8.09—Unverified
3Latent ODETest Error5.98—Unverified
4Latent SDETest Error4.03—Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.17—Unverified
2FVSLPIPS0.09—Unverified
3DMVFNLPIPS0.06—Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.32—Unverified
2FVSLPIPS0.18—Unverified
3DMVFNLPIPS0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.08—Unverified
2DMVFNLPIPS0.04—Unverified
3OPTLPIPS0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1ODE2VAETest Error93.07—Unverified
2ODE2VAE-KLTest Error15.99—Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.23—Unverified
2DMVFNLPIPS0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MGP-VAE (with geodesic loss)MSE4.5—Unverified
#ModelMetricClaimedVerifiedStatus
1SRVPFVD222—Unverified
#ModelMetricClaimedVerifiedStatus
1MCnet [villegas2017mcnet]LPIPS0.22—Unverified
#ModelMetricClaimedVerifiedStatus
1MGP-VAE (with geodesic loss)MSE61.6—Unverified
#ModelMetricClaimedVerifiedStatus
1SDCNetAverage PSNR37.15—Unverified