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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 394 papers

TitleStatusHype
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsCode0
Model-Based Reinforcement Learning for AtariCode0
Motion Graph Unleashed: A Novel Approach to Video PredictionCode0
Adversarial Video Generation on Complex DatasetsCode0
Eidetic 3D LSTM: A Model for Video Prediction and BeyondCode0
Simplifying Latent Dynamics with Softly State-Invariant World Models—0
101 Billion Arabic Words Dataset—0
Cubic LSTMs for Video Prediction—0
3D Motion Decomposition for RGBD Future Dynamic Scene Synthesis—0
Action Concept Grounding Network for Semantically-Consistent Video Generation—0
Modular Action Concept Grounding in Semantic Video Prediction—0
Action-conditioned Deep Visual Prediction with RoAM, a new Indoor Human Motion Dataset for Autonomous Robots—0
Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy—0
Aether: Geometric-Aware Unified World Modeling—0
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction—0
AID: Adapting Image2Video Diffusion Models for Instruction-guided Video Prediction—0
Allo-centric Occupancy Grid Prediction for Urban Traffic Scene Using Video Prediction Networks—0
A Log-likelihood Regularized KL Divergence for Video Prediction with A 3D Convolutional Variational Recurrent Network—0
AMPLIFY: Actionless Motion Priors for Robot Learning from Videos—0
A Review on Deep Learning Techniques for Video Prediction—0
A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches—0
Autoregressive Latent Video Prediction with High-Fidelity Image Generator—0
Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks—0
Can Learned Frame-Prediction Compete with Block-Motion Compensation for Video Coding?—0
CarbonNet: How Computer Vision Plays a Role in Climate Change? Application: Learning Geomechanics from Subsurface Geometry of CCS to Mitigate Global Warming—0
CausalVE: Face Video Privacy Encryption via Causal Video Prediction—0
CDNet: A cascaded decoupling architecture for video prediction—0
Combining Vision and Tactile Sensation for Video Prediction—0
Conditional Temporal Variational AutoEncoder for Action Video Prediction—0
Consistent Generative Query Networks—0
Consistent Jumpy Predictions for Videos and Scenes—0
Consistent World Models via Foresight Diffusion—0
ContextVP: Fully Context-Aware Video Prediction—0
Continuous Video Process: Modeling Videos as Continuous Multi-Dimensional Processes for Video Prediction—0
Controllable Video Generation With Sparse Trajectories—0
Convolutional Tensor-Train LSTM for Long-Term Video Prediction—0
CrevNet: Conditionally Reversible Video Prediction—0
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices—0
Data-Driven Uncertainty-Aware Forecasting of Sea Ice Conditions in the Gulf of Ob Based on Satellite Radar Imagery—0
Deep learning for spatio-temporal forecasting -- application to solar energy—0
Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks—0
Deep Variational Luenberger-type Observer for Stochastic Video Prediction—0
Deep Video Generation, Prediction and Completion of Human Action Sequences—0
Deep Video Prediction for Time Series Forecasting—0
Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning—0
Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning—0
Distributed solar generation forecasting using attention-based deep neural networks for cloud movement prediction—0
Diversity encouraged learning of unsupervised LSTM ensemble for neural activity video prediction—0
Diversity-Sensitive Conditional Generative Adversarial Networks—0
Dual Motion GAN for Future-Flow Embedded Video Prediction—0
Show:102550
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All datasetsKTHMoving MNISTKinetics-600 12 frames, 64x64Human3.6MCityscapes 128x128SynpickVPBAIR Robot PushingCMU Mocap-2CityscapesKITTIVimeo90KCMU Mocap-1

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
8SAVP (from SRVP)Cond10—Unverified
9SRVPCond10—Unverified
10SVG-LP (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
7Video TransformerCond5—Unverified
8MAGVIT (-L-FP)Cond5—Unverified
9DVD-GAN-FPCond5—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
3PredRNN++LPIPS0.05—Unverified
4PhyDNetLPIPS0.05—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