84 citations · 134 across the 10 of their papers we have counts for
10 papers
3D Point World Models: Point Completion Enables More Accurate Dynamics Learning
Skand Peri, Hung Nguyen, Chanho Kim +2
Learning predictive models of the world enables robotic control through planning, potentially allowing robots to improvise solutions on new tasks. However, large video-based dynami…
Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control
Skand Peri, Akhil Perincherry, Bikram Pandit +1
Efficient robot control often requires balancing task performance with energy expenditure. A common approach in reinforcement learning (RL) is to penalize energy use directly as pa…
Point Cloud Models Improve Visual Robustness in Robotic Learners
Skand Peri, Iain Lee, Chanho Kim +3
Visual control policies can encounter significant performance degradation when visual conditions like lighting or camera position differ from those seen during training -- often ex…
Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim +2
Object-centric world models provide structured representation of the scene and can be an important backbone in reinforcement learning and planning. However, existing approaches suf…
Improving Generative Imagination in Object-Centric World Models
Zhixuan Lin, Yi-Fu Wu, Skand Peri +3
The remarkable recent advances in object-centric generative world models raise a few questions. First, while many of the recent achievements are indispensable for making a general…
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri +5
The ability to decompose complex multi-object scenes into meaningful abstractions like objects is fundamental to achieve higher-level cognition. Previous approaches for unsupervise…
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
Deepak Babu Sam, Skand Vishwanath Peri, Mukuntha Narayanan Sundararaman +2
We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm. Typical counting models predict crowd density for…
Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet)
Jatin Garg, Skand Vishwanath Peri, Himanshu Tolani +1
Learning from different modalities is a challenging task. In this paper, we look at the challenging problem of cross modal face verification and recognition between caricature and…
MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net For Multi-Modal Alzheimer's Classification
Apoorva Sikka, Skand Vishwanath Peri, Deepti. R. Bathula
Recent studies suggest that combined analysis of Magnetic resonance imaging~(MRI) that measures brain atrophy and positron emission tomography~(PET) that quantifies hypo-metabolism…
DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild
Skand Vishwanath Peri, Abhinav Dhall
This paper describes our approach for the Disguised Faces in the Wild (DFW) 2018 challenge. The task here is to verify the identity of a person among disguised and impostors images…