Ali Marjaninejad — accepted AI-conference papers

2026

RMIR: A Benchmark Dataset for Reasoning-Intensive Multimodal Image Retrieval

Yijiang Li, Kunal Kotian, Ali Marjaninejad, Meir Friedenberg, Kaushik Pavani, Sunny Dasgupta

CVPR 2026

Current multimodal image retrieval benchmarks focus on relatively simple queries where target images are either described directly or by simple composition with an input image. When retrieval requires complex reasoning to determine the target image, the task becomes significantly more challenging, y

Cited by 0 Source ↗code ↗Scholar ↗

2020

A Bio-Inspired Framework for Joint Angle Estimation from Non-Collocated Sensors in Tendon-driven Systems

Daniel A. Hagen, Ali Marjaninejad, Francisco J. Valero Cuevas

IROS 2020

Estimates of limb posture are critical for the control of robotic systems. This is generally accomplished by utilizing on-location joint angle encoders which may complicate the design, increase limb inertia, and add noise to the system. Conversely, some innovative or smaller robotic morphologies can

Cited by 2 Source ↗Scholar ↗