Vision Projects
Advancing image understanding and generation with focus on efficiency
Image Understanding
Advancing image analysis and understanding capabilities
New Image Embeddings
Q4 2024 - Q3 2025
Developing improved image representation techniques
Key Outcomes
- Novel embedding architecture
- Cross-modal compatibility
- Cultural context awareness
- Efficient computation
Future Plans
- Scale to larger datasets
- Add more domains
- Improve efficiency
- Create visualization tools
Key Metrics
Dimension
1.0K
Speed
5ms/image
Accuracy
94%
Compression
75%
Image to Text
Q4 2024 - Q4 2025
Creating accurate image captioning systems in Telugu
Key Outcomes
- Telugu caption generation
- Cultural context awareness
- Multi-lingual support
- Style control
Future Plans
- Expand language support
- Improve accuracy
- Add style variants
- Create demo platform
Key Metrics
Languages
5
Bleu Score
38.5
Latency
200ms
Accuracy
92%
Generation & Retrieval
Creating efficient image generation and retrieval systems
Low-Resource Image Generation
Q2 2024 - Q4 2025
Developing efficient image generation models
Key Outcomes
- Lightweight architecture
- Mobile optimization
- Quality metrics
- Style preservation
Future Plans
- Reduce model size
- Improve generation speed
- Add more styles
- Create mobile SDK
Key Metrics
Model Size
2GB
Gen Time
2s
Fid
18.5
Styles
10
Image RAG Systems
Q3 2024 - Q4 2025
Building retrieval-augmented generation for images
Key Outcomes
- Retrieval pipeline
- Context integration
- Multi-modal search
- Quality filters
Future Plans
- Scale image database
- Improve relevance
- Add semantic search
- Create API
Key Metrics
Db Size
10M images
Recall
95%
Latency
100ms
Precision
92%
Performance Metrics
Key indicators of our vision technologies
Model Efficiency
Average Model Size
2.5GB -40%
Inference Time
150ms -25%
Memory Usage
4GB -30%
Quality Metrics
FID Score
18.5 +15%
BLEU Score
38.5 +12%
User Satisfaction
4.6/5 +8%
Core Technologies
Efficient Architectures
Optimized model architectures for low-resource environments
- Mobile-first design
- Memory optimization
- Battery efficiency
- Edge deployment
Cultural Context
Systems designed for Indian visual elements and context
- Local style awareness
- Cultural preservation
- Context sensitivity
- Regional adaptation
Multi-modal Integration
Seamless integration of vision and language
- Cross-modal learning
- Joint representations
- Unified processing
- Context transfer