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Loss Function - Generator
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Classroom Contents
Video Content Understanding Using Text
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- 1 Intro
- 2 Motivation
- 3 Challenges
- 4 Algorithm
- 5 Training
- 6 Video Representation
- 7 Scoring function
- 8 Optimization - Updating Rules
- 9 Exemplar queries
- 10 Test on Unseen Queries
- 11 Qualitative results
- 12 Sentence Encoder
- 13 Spatial Attention Network • Which regions of the frames to look?
- 14 Temporal Attention Model
- 15 Inference Module
- 16 Experiments
- 17 Limitations
- 18 What is an Inaccuracy?
- 19 Formulation
- 20 Detection By Reconstruction
- 21 Visual Features
- 22 Inaccuracy Detection
- 23 Correction
- 24 Last two chapters
- 25 How about the opposite problem?
- 26 Problem Definition
- 27 Proposed Approach - Generator Block Diagram
- 28 Text Encoding
- 29 Start and End Distributions
- 30 Latent Path Construction
- 31 Conditional BatchNormalization (CBN)
- 32 Frame Generation
- 33 UpPooling Block Details
- 34 Proposed Approach - Discriminator
- 35 Loss Function - Generator
- 36 Hinge GAN-Loss on Discriminator
- 37 Evaluation Metrics
- 38 A2D Quantitative Results
- 39 A2D Results
- 40 Robotic Results
- 41 Dissertation Summary
- 42 Future Work
