Even with advanced AI video generation models, results may not always match your expectations. This guide addresses common challenges and provides practical solutions to help you achieve the best possible results with Scenario's video generation capabilities.
Understanding Video Generation Limitations
Before diving into specific issues, it's important to understand the inherent limitations of current video generation technology:
Duration: Most models generate 5-12 seconds of footage (varies by model)
Resolution: Often limited to 480p, 720p, or 1080p (model-dependent)
Complexity: More complex scenes may show reduced quality or consistency
Style: Some visual styles translate to video more effectively than others
With these limitations in mind, let's explore specific issues and their solutions.
1. Visual Quality Issues
Blurry or Low-Detail Output
Why it happens: This typically occurs when using lower-resolution models, creating overly complex scenes, or when the model struggles with certain visual styles.
How to fix it:
Switch to higher-resolution models like Pixverse V4.5 (1080p) or Wan 2.1 I2V 720p for detail-critical work.
Simplify your scene by focusing on fewer key elements and reducing background complexity.
Enhance detail descriptions with specific textures and materials, using phrases like "highly detailed" or "sharp focus."
Upscale your input image.
Visual Artifacts or Glitches
Why it happens: Artifacts often appear when models struggle with complex elements, receive conflicting instructions, or encounter technical limitations with specific visual elements.
How to fix it:
Identify which specific elements show artifacts and simplify or remove them in your next generation.
Clarify your prompt by removing contradictory descriptions and prioritizing clear, consistent direction.
Different models handle visual elements differently—Veo 2 produces fewer artifacts in natural scenes, while Minimax Video-01 Live shows fewer artifacts in character animation.
2. Motion Quality Issues
Unnatural or Jerky Movement
Why it happens: Poor motion quality typically stems from insufficient motion description, model limitations with complex movement, or conflicting motion instructions.
How to fix it:
Improve your motion descriptions by being specific about type, speed, and quality of movement.
Use physics-based terminology like "gently swaying" or "smoothly rotating" and describe complete motion paths.
Choose motion-optimized models: Minimax Video-01 Live excels at natural character movement, Veo 2 demonstrates superior physics understanding, and Pixverse V4.5 handles complex multi-element motion well.
Static or Minimal Movement
Why it happens: This occurs when motion descriptions are insufficient, the model conservatively interprets ambiguous instructions, or the prompt focuses too much on static elements.
How to fix it:
Explicitly state what should move and how, using active, dynamic language throughout your prompt.
Place motion descriptions early and avoid overemphasizing static qualities.
Try motion-forward models like Kling v2.0 or Pixverse V4.5 with camera movement instructions. Include references to movement-heavy concepts ("dynamic," "kinetic," "flowing") or environmental factors that imply movement ("windy conditions," "underwater currents").
Consistency Issues
Elements Changing or Flickering
Why it happens: Temporal consistency limitations, complex or ambiguous elements, and conflicting descriptions can all lead to elements changing appearance throughout the video.
How to fix it:
Choose consistency-focused models like Minimax Video-01 Live, Veo 2, or Wan 2.1 I2V 720p.
Simplify complex elements by reducing the number of detailed elements that must remain consistent.
Be explicit about which elements must maintain consistency throughout the video.
Style Inconsistency
Why it happens: Style inconsistency often stems from ambiguous style descriptions, styles that are challenging to maintain in motion, or model limitations with certain artistic approaches.
How to fix it:
Choose style-appropriate models: Kling v2.0 excels at maintaining artistic and anime styles, Pixverse V4.5 demonstrates good style consistency across various aesthetics, and Minimax Video-01-Director maintains cinematic styles effectively.
Be specific about your desired visual style and reinforce stylistic language throughout your prompt.
For image-to-video, ensure your reference image already embodies your desired style—consider generating a styled image first, then animating it.
3. Camera and Composition Issues
Unwanted Camera Movement
Why it happens: This may be the default behavior of some models, result from ambiguous camera instructions, or occur when the model interprets a scene as requiring camera movement.
How to fix it:
Explicitly request a static camera using phrases like "static shot," "fixed camera," or "camera remains still" early in your prompt.
Choose camera-control models like Minimax Video-01-Director or Pixverse V4.5. Clearly distinguish between subject movement and camera movement, using language like "while the camera remains fixed."
Reference static cinematography terms like "tripod shot" or "locked-down camera."
Undesired Composition Changes
Why it happens: Models may reinterpret scenes during animation, especially with insufficient composition description or movements that require composition adjustment.
How to fix it:
Be explicit about framing and arrangement of elements, specifying which elements should remain in specific positions.
Choose composition-stable models like Wan 2.1 I2V 720p, Minimax Video-01 Live, or Veo 2.
Limit extreme movements that would naturally change composition and request subtle movements that work within the established frame.
Ensure your reference image has the exact composition you want, with appropriate space for planned movement.
4. Prompt Adherence Issues
Results Don't Match Prompt Description
Why it happens: Overly complex or contradictory prompts, model limitations with certain concepts, or prompt structure prioritizing the wrong elements can all lead to mismatched results.
How to fix it:
Simplify and prioritize by focusing on fewer key instructions and placing the most important elements early in your prompt.
Choose prompt-adherent models like Veo 2, Pixverse V4.5, or Kling v2.0.
Use clear, unambiguous language, avoiding metaphorical or highly abstract descriptions.
Important Elements Missing or Minimized
Why it happens: This typically occurs with insufficient emphasis in the prompt, competing elements drawing focus, or model limitations with specific elements.
How to fix it:
Emphasize key elements by mentioning them multiple times, describing them in detail, and placing them early in your prompt.
Reduce competing elements by simplifying or removing less important aspects.
Use compositional language like "prominently featured," "focal point," or "centered" to specify where important elements should appear.
5. Advanced Troubleshooting Techniques
A/B Testing Approach
For systematic improvement, isolate variables by changing only one aspect of your prompt at a time and testing different phrasings for the same concept. Document and analyze all test variations, noting specific improvements or issues and identifying patterns in what works. Build on success by expanding from effective approaches and developing templates based on proven patterns.
Prompt Engineering Patterns
Certain structural approaches often solve common issues:
The Specificity Pattern (solves: Vague results, inconsistent style, poor composition)👇
[Detailed subject description] [specific action/movement] in [detailed environment]. [Lighting description]. [Camera instruction]. [Style reference].
The Priority Pattern (solves: Missing key elements, focus on wrong aspects)👇
Most important: [critical element]. [Secondary elements]. Camera [movement type] to follow [subject] as it [action]. Style is [specific aesthetic].
The Physics Pattern (solves: Unnatural movement, poor physical interactions)👇
[Subject] [action] with realistic physics. [Material] responds naturally to [forces]. [Environmental elements] move according to natural principles
The Consistency Pattern (solves: Flickering, changing elements, inconsistent details)👇
[Subject] maintains consistent appearance throughout the video. [Distinctive features] remain unchanged while [specific elements] move naturally.
Model-Specific Troubleshooting
Different models require specific approaches:
Minimax Models:
For Video-01: Emphasize cinematic quality and dramatic lighting for more impact
For Video-01-Director: Use bracketed commands [Pan left] rather than descriptive text for camera movements
For Video-01 Live: Focus on emotional state rather than physical description for natural character expressions
Kling Models:
For v1.6: Explicitly request "vibrant colors" and "high contrast" if colors appear washed out
For v1.6 Pro: Reinforce style references throughout the prompt for better style consistency
For v2.0: Request "subtle" or "natural" motion explicitly if movement seems exaggerated
Pixverse Models:
For V4: Specify target platform more clearly for platform-specific content
For V4.5: Use Fusion syntax to define relationships in multi-subject scenes
Other Models:
For Veo 2: Describe physical properties of materials explicitly for natural physics
For Wan 2.1: Mention plans to use frame interpolation if 16 FPS appears choppy
For Luma Ray models: Be very explicit about lighting conditions if generation is too dark or bright
When to Try a Different Approach
Sometimes the most efficient solution is to pivot:
Switch Input Types:
If text-to-video isn't working, try creating a reference image first. If image-to-video isn't preserving key elements, add more explicit text guidance.
Change Models:
Different models have different strengths—if you've tried multiple prompt variations without success, try a different model optimized for your content type.
Simplify Your Concept:
Some ideas may exceed current capabilities. Breaking complex concepts into simpler components often yields better results.
Combine AI and Traditional Techniques:
For some projects, using AI for certain elements and traditional animation or video editing for others may produce the best results.
6. Troubleshooting Decision Tree
START → Is the issue with visual quality?
├── YES → Is it blurry/low-detail?
│ ├── YES → Try higher-resolution model + simplify scene + enhance detail descriptions
│ └── NO → Is it showing artifacts/glitches?
│ └── YES → Identify problematic elements + clarify prompt + try different model
└── NO → Is the issue with motion?
├── YES → Is movement unnatural/jerky?
│ ├── YES → Improve motion descriptions + choose motion-optimized model
│ └── NO → Is there minimal/no movement?
│ └── YES → Use explicit motion language + try motion-forward models
└── NO → Is the issue with consistency?
├── YES → Are elements changing/flickering?
│ ├── YES → Choose consistency-focused model + simplify complex elements
│ └── NO → Is style inconsistent?
│ └── YES → Choose style-appropriate model + be specific about style
└── NO → Is the issue with camera/composition?
├── YES → Is there unwanted camera movement?
│ ├── YES → Request static camera + choose camera-control model
│ └── NO → Are there composition changes?
│ └── YES → Be explicit about composition + limit extreme movements
└── NO → Is the issue with prompt adherence?
├── YES → Results don't match prompt?
│ ├── YES → Simplify/prioritize + use clear language
│ └── NO → Important elements missing?
│ └── YES → Emphasize key elements + reduce competing elements
└── NO → Try A/B testing + prompt patterns + model-specific approaches
By systematically addressing these common issues, you can significantly improve your video generation results. Remember that AI video generation is still an evolving tech - some limitations are inherent to current models, but creative problem-solving and iterative refinement can help you achieve impressive results despite these constraints.
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