IEEE ICIP 2025 Website | Date TBA | 2025 VIP Cup Official Document
[Sponsored by the IEEE Signal Processing Society]

Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have gained significant prominence in recent years due to their diverse applications in areas such as surveillance, delivery, agriculture, logistics, disaster response, and military operations. However, the proliferation of drones has also introduced critical challenges such as unauthorized aerial activity, potential threats from payload delivery systems including payload delivery for malicious purposes as well as major security and privacy concerns. This necessitates the detection and tracking of drones, along with the identification of their payloads to ensure safety and security, particularly in sensitive or restricted areas.

Traditional vision-based approaches for drone detection predominantly rely on RGB images, which are often hindered by environmental factors such as low light, fog, or glare. On the other hand, infrared (IR) imaging provides complementary information by capturing thermal signatures enabling robust detection in challenging conditions such as nighttime or occlusion even in cases where the drones are exceedingly far from the field of view (FoV) of the surveillance cameras. Although it may seem that infrared imaging outperforms RGB imaging in such cases, standalone use of IR data may lack the spatial and textural richness provided by RGB images. This makes it essential to combine the two modalities to leverage their complementary strengths.

Alongside drone detection, the ability to detect and identify payloads carried by drones is critical due to the potential risks associated with unauthorized or malicious payload delivery. Payloads may include hazardous materials, surveillance equipment, or contraband, posing threats to public safety, security, and privacy. Identifying payloads in real-time enables proactive measures to mitigate risks making it an essential aspect of drone monitoring systems. However, identifying and analyzing payloads carried by drones poses unique challenges. Payloads may vary in size, shape and thermal properties making it difficult to rely on a single modality for robust detection. RGB imaging provides critical visual cues for recognizing payload shapes and textures while IR imaging can highlight heat signatures of payloads, particularly those carrying heat-generating devices or components. A fusion-based approach is therefore crucial to enhance payload detection accuracy and reliability.

• Each team MUST be composed of: (i) One faculty member (the Supervisor) and (ii) At least 3 but no more than 10 undergraduates; Optionally (iii) At most one graduate student (the Tutor).
  • At least three of the undergraduate team members must be SPS student members at time of team registration.
• Further definitions of each team position are as follows:
  • Faculty (Supervisor): Postdocs and research associates are not considered as faculty members.
  • Graduate Student (Tutor): A graduate student is a student having earned at least a 4-year University degree at the time of submission. Please note: Tutors are not eligible to receive travel grants or prize money.
  • Undergraduate: An undergraduate student is a student without a 4-year degree.
• Team members cannot be changed after the team registration deadline.
• At least one undergraduate team member must be in attendance (in-person) of the final round of the competition held at the respective conference (IICIP) to present the team’s work.*

The three teams with the highest performance in the open competition based on the judging criteria will be selected as finalists and invited to participate in the final competition at ICIP. The champion team will receive a Grand Prize of $5,000. The first and the second runner-up teams will receive a prize of $2,500 and $1,500, respectively, in addition to travel grants and complimentary conference registrations for up to three undergraduate team members.

Team Registration Deadline: 30 April 2025 (Register here)
Availability of Test Data – 20 May 2025
Final submission due: 15 June 2025
Announcement of 3 finalist teams: 15 July 2025
Final competition at ICIP 2025: 14-17 September 2025

Official SP Cup Team Registration: All teams must be registered through the official competition in order to be considered as a participating team.

Official team registration can be submitted via: https://www2.securecms.com/VIPCup/VIPRegistration.asp

All teams MUST read, understand, and agree to the SPS Student Competition Terms & Conditions at the time of team registration to be eligible for the competition.

Vishnu Ravishankar, Software Development Engineer, ARTPARK, Indian Institute of Science, India
Dharini Raghavan, Graduate Student, Georgia Institute of Technology, Atlanta, USA
Dr S Sethu Selvi, Professor, Department of ECE, Ramaiah Institute of Technology, India
Dr Raghuram S, Associate Professor, Department of ECE, Ramaiah Institute of Technology, India
Dr. Sitaram Ramachandrula, Senior Director, Data Science, [24]7.ai, India
Shefali Singh, Student Department of ECE, Ramaiah Institute of Technology, India
Sangeetha Kar, Student Department of ECE, Ramaiah Institute of Technology, India
Suman Jangid, Student Department of ECE, Ramaiah Institute of Technology, India