1. WEEK 4 PRESENTATION
NGOC TA
AIDEAN SHARGHI

2. SST: Single-Stream Temporal Action Proposals
Single pass
Input: video sentence
Output: number of temporal intervals that contain an action
Dataset: THUMOS 14 (20min long videos)
Performs better at higher tIoU regime
Handle very long testing sequences

3. Dense-Captioning Events in Videos
Localize temporal proposal of interest
Describe with natural language
Dataset: ActivityNet Captions
Single pass
Using more strides improves recall across all values of IoU’s

4. Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning
Learn the details
Modify parameters

5. Output sentences:
a man is seen speaking to the camera and leads into a person holding a ball and a man is standing in a large group of people
a man is seen speaking to the camera and leads into a man holding a stick and a man is standing in a black
METEOR:

6. Extract features from C3D Model
axon-research/c3d-keras
facebook/C3D -caffe
hx173149/C3D-tensorflow

7. THANK YOU