Person attribute recognition (PAR) is crucial for city surveillance as it enables the identification and tracking of individuals across multiple cameras. It also gives the system the ability to retrieve instances that have specific attributes, a crucial requirement in surveillance applications. Typical attributes include gender, clothing style, carrying items, etc, which provide high-level semantic information. Existing standard datasets like PETA, Market 1501, and PA100K lack attribute classes relevant to Indian attire, such as kurta, salwar, dupatta, and saree, etc, which are essential for the Indian context. Several solutions are also available in the literature which gives good results on these datasets. But these solutions are not directly applicable to the Indian scenario where there is a change in skin color, dressing style, etc. Even the class information needs to be modified to suit the Indian scenario. The proposed challenge addresses this gap by focusing on detecting person attributes explicitly tailored for the Indian scenario, enhancing the accuracy and relevance of attribute recognition in smart city environments. We will be providing a sample dataset with the intent of sensitizing the participants of the Indian scenario. Participants are encouraged to enhance the dataset to meet their training requirements in a suitable manner.
In today’s digital era, the presence of a PAR system holds immense importance in both civilian and military applications. Such systems allow for the identification of individuals based on specific attributes within surveillance videos, a capability crucial for security purposes. With the widespread deployment of surveillance cameras in smart cities, as well as in residential and commercial settings, the need for robust PAR solutions is more pressing than ever. While existing solutions may perform well on curated datasets, the real challenge lies in developing systems that can handle the complexity of real-world data. This challenge serves as an opportunity for researchers to collaborate and create practical, effective PAR solutions tailored to the Indian context, leveraging the collective knowledge and expertise of the research community.
Interested in participation? Please Click Here to register.
Event | Date |
---|---|
Registration opening and launch of challenge website | May 1, 2024 |
Release of Training Dataset | May 15, 2024 |
Opening Date for Submission to Challenges | May 28, 2024 |
Release of Test Set Images | May 28, 2024 |
Closing Date for Submission to Challenges | June 24, 2024 |
Last Date to Submit a Write-up About the Submitted Solution: July 1, 2024 (via Email) | July 1, 2024 |
Winner announcement | July 8, 2024 |
Test Set-1 (Shared with Participant) Last updated: 26th June 2024
S.No. | Task/Team Name | Mean Accuracy (mA) |
---|---|---|
1 | Baseline (Vehant) | 0.77 |
2 | [blank] | 0.83 |
3 | EagleEye | 0.82 |
4 | Visionary | 0.74 |
5 | eVision | 0.74 |
6 | TraficVision | 0.71 |
7 | Invisible | 0.64 |
8 | ihdavjar | 0.65 |
9 | VisionMission | 0.49 |
Test Set-2 (Vehant internal large test dataset), Last updated: 26th June 2024
S.No. | Task/Team Name | Mean Accuracy (mA) |
---|---|---|
1 | Baseline (Vehant) | 0.72 |
2 | [blank] | 0.67 |
3 | EagleEye | 0.64 |
4 | eVision | 0.63 |
5 | Visionary | 0.62 |
6 | TraficVision | 0.61 |
7 | Invisible | 0.57 |
8 | ihdavjar | 0.57 |
9 | VisionMission | 0.49 |
Position | Prize Amount (in INR) |
---|---|
1st Place (Winner) | 20,000 |
2nd Place | 15,000 |
3rd Place | 5,000 |
Position | Team Name | Presentation |
---|---|---|
1st Place (Winner) | [blank] | Oral & Poster |
2nd Place | Visionary | Oral & Poster |
3rd Place | Trafic Vision | Oral & Poster |
- | EagleEye | Poster |
- | eVision | Poster |
Session Topic | Speaker | Duration |
---|---|---|
Research in Video Analytics at Vehant: Driving Innovation and Efficiency | Dr. Shikha | 25 min |
SCSPAR24 | Abhay | 20 min |
SCSPAR24 Demo | - | 5 min |
Challenge winner 1 | Team [blank] | 15 min |
Challenge winner 2 | Team Visionary | 15 min |
Poster session | - | 10 min |
Organizer : Renu M. Rameshan, Shikha Gupta, Shivam Nigam, Abhay Kumar, Swati Pandey
For any query please contact:-
mailto:contest@vehant.com