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 301350 of 394 papers

TitleStatusHype
ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge0
Whole-Body Conditioned Egocentric Video Prediction0
Wide and Narrow: Video Prediction from Context and Motion0
Wildfire Forecasting with Satellite Images and Deep Generative Model0
Zero-Episode Few-Shot Contrastive Predictive Coding: Solving intelligence tests without prior training0
10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver0
SRVP: Strong Recollection Video Prediction Model Using Attention-Based Spatiotemporal Correlation FusionCode0
A Dataset To Evaluate The Representations Learned By Video Prediction ModelsCode0
VarNet: Exploring Variations for Unsupervised Video PredictionCode0
Folded Recurrent Neural Networks for Future Video PredictionCode0
Flow-Grounded Spatial-Temporal Video Prediction from Still ImagesCode0
Compositional Video PredictionCode0
Stochastic Adversarial Video PredictionCode0
Fast Fourier Inception Networks for Occluded Video PredictionCode0
Exploring Temporal Information for Improved Video UnderstandingCode0
Stochastic Video Generation with a Learned PriorCode0
PredNet and Predictive Coding: A Critical ReviewCode0
Expert Gate: Lifelong Learning with a Network of ExpertsCode0
Video-to-Video SynthesisCode0
Event-driven Video Frame SynthesisCode0
Entity Abstraction in Visual Model-Based Reinforcement LearningCode0
Eidetic 3D LSTM: A Model for Video Prediction and BeyondCode0
Adversarial Video Generation on Complex DatasetsCode0
Dynamic Filter NetworksCode0
T3VIP: Transformation-based 3D Video PredictionCode0
Physics-Informed Deep Neural Networks for Transient Electromagnetic AnalysisCode0
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from VideoCode0
Predcnn: Predictive learning with cascade convolutionsCode0
Pair-wise Layer Attention with Spatial Masking for Video PredictionCode0
Predicting Deeper into the Future of Semantic SegmentationCode0
Predicting Future Frames Using Retrospective Cycle GANCode0
Predicting Future Instance Segmentation by Forecasting Convolutional FeaturesCode0
CMS-LSTM: Context Embedding and Multi-Scale Spatiotemporal Expression LSTM for Predictive LearningCode0
CloudCast: A Satellite-Based Dataset and Baseline for Forecasting CloudsCode0
Action-conditioned Benchmarking of Robotic Video Prediction Models: a Comparative StudyCode0
Order Matters: Shuffling Sequence Generation for Video PredictionCode0
Disentangling Propagation and Generation for Video PredictionCode0
Prediction Under Uncertainty with Error-Encoding NetworksCode0
Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive LearningCode0
Predictive Coding Based Multiscale Network with Encoder-Decoder LSTM for Video PredictionCode0
ODE^2VAE: Deep generative second order ODEs with Bayesian neural networksCode0
Object-centric Video Prediction without AnnotationCode0
Deep Visual Foresight for Planning Robot MotionCode0
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMsCode0
Neural Multigrid Memory For Computational Fluid DynamicsCode0
Temporal View Synthesis of Dynamic Scenes through 3D Object Motion Estimation with Multi-Plane ImagesCode0
VideoFlow: A Conditional Flow-Based Model for Stochastic Video GenerationCode0
The Pose Knows: Video Forecasting by Generating Pose FuturesCode0
Programmatic Video Prediction Using Large Language ModelsCode0
DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big EventsCode0
Show:102550
← PrevPage 7 of 8Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Struct-VRNN (from Grid-keypoints)FVD395Unverified
2SV2P time-invariant (from Grid-keypoints)FVD253.5Unverified
3SV2P time-invariant (from Grid-keypoints)FVD209.5Unverified
4SAVP (from Grid-keypoints)FVD183.7Unverified
5SVG-LP (from Grid-keypoints)FVD157.9Unverified
6SAVP-VAE (from Grid-keypoints)FVD145.7Unverified
7Grid-keypointsFVD144.2Unverified
8SVG-LP (from SRVP)Cond10Unverified
9SLAMPCond10Unverified
10SAVP (from SRVP)Cond10Unverified
#ModelMetricClaimedVerifiedStatus
1ConvLSTMMSE103.3Unverified
2PredRNNMSE56.8Unverified
3MIMMSE52Unverified
4PredRNN-V2MSE48.4Unverified
5Causal LSTMMSE46.5Unverified
6MIM*MSE44.2Unverified
7SA-ConvLSTMMSE43.9Unverified
8LMCMSE41.5Unverified
9E3D-LSTMMSE41.3Unverified
10CrevNet+ConvLSTMMSE38.5Unverified
#ModelMetricClaimedVerifiedStatus
1LVTFVD224.73Unverified
2OmniTokenizer-ARFVD32.9Unverified
3RaMViDFVD16.46Unverified
4RIN (400 steps)FVD11.5Unverified
5RIN (1000 steps)FVD10.8Unverified
6LARPFVD5.1Unverified
7DVD-GAN-FPCond5Unverified
8MAGVIT (-L-FP)Cond5Unverified
9MAGVIT (-B-FP)Cond5Unverified
10TriVD-GAN-FPCond5Unverified
#ModelMetricClaimedVerifiedStatus
1IAM4VPSSIM0.94Unverified
2SwinLSTMSSIM0.91Unverified
3FFINetSSIM0.91Unverified
4SimVPSSIM0.9Unverified
5PhyDNetSSIM0.9Unverified
6E3D-LSTMSSIM0.87Unverified
7MIMSSIM0.79Unverified
8PredRNNSSIM0.78Unverified
9FRNNSSIM0.77Unverified
#ModelMetricClaimedVerifiedStatus
1SVG (from Hier-VRNN)FVD1,300.26Unverified
2Hier-VRNNFVD567.51Unverified
3SLAMPCond.10Unverified
4SRVPCond.10Unverified
5GHVAEsCond.2Unverified
#ModelMetricClaimedVerifiedStatus
1SVG-DetLPIPS0.07Unverified
2SVG-LPLPIPS0.07Unverified
3PhyDNetLPIPS0.05Unverified
4PredRNN++LPIPS0.05Unverified
5MSPredLPIPS0.03Unverified
#ModelMetricClaimedVerifiedStatus
1DVGFVD120.03Unverified
2DVD-GAN-FPFVD109.8Unverified
3PhenakiFVD97Unverified
4MMVGFVD85.2Unverified
#ModelMetricClaimedVerifiedStatus
1ODE2VAETest Error10.06Unverified
2ODE2VAE-KLTest Error8.09Unverified
3Latent ODETest Error5.98Unverified
4Latent SDETest Error4.03Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.17Unverified
2FVSLPIPS0.09Unverified
3DMVFNLPIPS0.06Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.32Unverified
2FVSLPIPS0.18Unverified
3DMVFNLPIPS0.11Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.08Unverified
2DMVFNLPIPS0.04Unverified
3OPTLPIPS0.04Unverified
#ModelMetricClaimedVerifiedStatus
1ODE2VAETest Error93.07Unverified
2ODE2VAE-KLTest Error15.99Unverified
#ModelMetricClaimedVerifiedStatus
1DVFLPIPS0.23Unverified
2DMVFNLPIPS0.1Unverified
#ModelMetricClaimedVerifiedStatus
1MGP-VAE (with geodesic loss)MSE4.5Unverified
#ModelMetricClaimedVerifiedStatus
1SRVPFVD222Unverified
#ModelMetricClaimedVerifiedStatus
1MCnet [villegas2017mcnet]LPIPS0.22Unverified
#ModelMetricClaimedVerifiedStatus
1MGP-VAE (with geodesic loss)MSE61.6Unverified
#ModelMetricClaimedVerifiedStatus
1SDCNetAverage PSNR37.15Unverified