ECS174-L16

📗 -> Lecture Date: Name

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Slides

🎤 Vocab

❗ Unit and Larger Context

Small summary

✒️ -> Scratch Notes

Object Detection

single Object?

-> Treat localization as a regression problem!

Multiple Objects?

• Each image needs a different number of outputs
  -> Apply a CNN to many different crops of the image, CNN classifies each crop as object
  or background

Region Selection

In order to not have to do a CNN for a massive amount of potential crops (for multiple object search)…
-> find “blobby” regions likely to contain objects

R-CNN

Make CNN do roposas
Region Proposal Network (RPN) to redict proposals from features

• Otherwise same as Fast R-CNN
  • Crop features for each proposal, classify each one
  • Basically train a classifier to detect object

Bipartite: 2 sets of N objects, cost between association object i to j has a cost.

• Stable Marriage: Each object in each set tied to 1 and only one 1 object in the other set
  • Find the marriage that minimizes cost, make it stable
  • Solution to this is the hungarian algorithm, O(n)

R-CNN Benchmarks for Test-Time Speed:

• R-CNN: 49
• SPP-Net: 4.3
• Fast R-CNN: 2.3
• Faster R-CNN: 0.2

Single-Stage Object Detectors: YOLO / SSD / RetinaNet

Input image

• 3 x H x W
  Divide image into grid
• 7 x 7
• Image a set of base boxes centered at each grid cell
  • Here B = 3
    Within each grid cell:
• Regress from each of the B base boxes to a final box with 5 numbers:
  • (dx, dy, dh, dw, confidence)
• Predict scores for each of C classes (including background as a class)
• Looks a lot like RPN, but category-specific!
  Output:
• 7 x 7 x (5 * B + C

Mask R-CNN (looks to identify something and give a mask outline (countour kind of))
Also does pose

Object Detection + Captioning = Dense Captioning

• Can extrapolate out to do dense video captioning

Objects + Relationships = Scene Graphs

• Captures relationships between objects
  • Painting is hanging on a wall
    • Painting -> Hanging -> Wall
  • Very useful for robotics

🔗 -> Links

Resources

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Connections

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