29 citations · 88 across the 17 of their papers we have counts for
21 papers
PhysMamba: Selective State Space Models as Learned Articulated Body Simulators
Haochuan Zhang, Sinisa Todorovic
We introduce the first learned articulated body simulator based on a selective state space model (SSM), called PhysMamba. PhysMamba predicts next-frame full-body state from positio…
iFS-RCNN: An Incremental Few-shot Instance Segmenter
Khoi Nguyen, Sinisa Todorovic
This paper addresses incremental few-shot instance segmentation, where a few examples of new object classes arrive when access to training examples of old classes is not available…
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
Arjun R. Akula, Keze Wang, Changsong Liu +5
We propose CX-ToM, short for counterfactual explanations with theory-of mind, a new explainable AI (XAI) framework for explaining decisions made by a deep convolutional neural netw…
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation
Khoi Nguyen, Sinisa Todorovic
This paper addresses weakly supervised amodal instance segmentation, where the goal is to segment both visible and occluded (amodal) object parts, while training provides only grou…
Action Shuffle Alternating Learning for Unsupervised Action Segmentation
Jun Li, Sinisa Todorovic
This paper addresses unsupervised action segmentation. Prior work captures the frame-level temporal structure of videos by a feature embedding that encodes time locations of frames…
Anchor-Constrained Viterbi for Set-Supervised Action Segmentation
Jun Li, Sinisa Todorovic
This paper is about action segmentation under weak supervision in training, where the ground truth provides only a set of actions present, but neither their temporal ordering nor w…