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 351394 of 394 papers

TitleStatusHype
Conditional COT-GAN for Video Prediction with Kernel SmoothingCode0
Video Frame Synthesis using Deep Voxel FlowCode0
Autoregression-free video prediction using diffusion model for mitigating error propagationCode0
Deep multi-scale video prediction beyond mean square errorCode0
Video Prediction via Selective SamplingCode0
Reduced-Gate Convolutional LSTM Using Predictive Coding for Spatiotemporal PredictionCode0
Mutual Information Based Method for Unsupervised Disentanglement of Video RepresentationCode0
Motion Graph Unleashed: A Novel Approach to Video PredictionCode0
A Temporally-Aware Interpolation Network for Video Frame InpaintingCode0
Model-Based Reinforcement Learning for AtariCode0
Video Pixel NetworksCode0
MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent NetworksCode0
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsCode0
ARMA Nets: Expanding Receptive Field for Dense PredictionCode0
Deep Learning for Precipitation Nowcasting: A Benchmark and A New ModelCode0
Scalable Adaptive Computation for Iterative GenerationCode0
Location Dependency in Video PredictionCode0
Let's Think Frame by Frame with VIP: A Video Infilling and Prediction Dataset for Evaluating Video Chain-of-ThoughtCode0
SDC-Net: Video prediction using spatially-displaced convolutionCode0
Learning to Generate Long-term Future via Hierarchical PredictionCode0
Understanding the Role of Weather Data for Earth Surface Forecasting using a ConvLSTM-based ModelCode0
Learning to Decompose and Disentangle Representations for Video PredictionCode0
Learning a Driving SimulatorCode0
Inception-inspired LSTM for Next-frame Video PredictionCode0
Action-Conditional Video Prediction using Deep Networks in Atari GamesCode0
Improved Conditional VRNNs for Video PredictionCode0
Decomposing Motion and Content for Natural Video Sequence PredictionCode0
Semantic Prediction: Which One Should Come First, Recognition or Prediction?Code0
VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric ManipulationCode0
CoPhy: Counterfactual Learning of Physical DynamicsCode0
Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context TranslationCode0
SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive LearningCode0
Unsupervised Keypoint Learning for Guiding Class-Conditional Video PredictionCode0
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal GenerationCode0
FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing GANsCode0
Unsupervised Learning for Physical Interaction through Video PredictionCode0
Frequency Domain Transformer Networks for Video PredictionCode0
Frame-wise Conditioning Adaptation for Fine-Tuning Diffusion Models in Text-to-Video PredictionCode0
Learning to Take Directions One Step at a TimeCode0
SME-Net: Sparse Motion Estimation for Parametric Video Prediction Through Reinforcement LearningCode0
Unsupervised Learning of Object Structure and Dynamics from VideosCode0
Understanding the Perceived Quality of Video PredictionsCode0
Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution ShiftsCode0
Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video PredictionCode0
Show:102550
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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