4 citations · 8 across the 9 of their papers we have counts for
4 papers · 1 filter
MIP-GAF: A MLLM-annotated Benchmark for Most Important Person Localization and Group Context Understanding
Surbhi Madan, Shreya Ghosh, Lownish Rai Sookha +4
Estimating the Most Important Person (MIP) in any social event setup is a challenging problem mainly due to contextual complexity and scarcity of labeled data. Moreover, the causal…
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
Weijie Tu, Weijian Deng, Liang Zheng +1
This work aims to develop a measure that can accurately rank the performance of various classifiers when they are tested on unlabeled data from out-of-distribution (OOD) distributi…
Authentic Emotion Mapping: Benchmarking Facial Expressions in Real News
Qixuan Zhang, Zhifeng Wang, Yang Liu +4
In this paper, we present a novel benchmark for Emotion Recognition using facial landmarks extracted from realistic news videos. Traditional methods relying on RGB images are resou…
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
Weijie Tu, Weijian Deng, Tom Gedeon
Contrastive Language-Image Pre-training (CLIP) models have demonstrated remarkable generalization capabilities across multiple challenging distribution shifts. However, there is st…