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20192026
most citedCOVID-19 on Social Media: Analyzing Misinformation in Twitter Conversations

137 citations · 233 across the 26 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

Query-adaptive Recurrent Tokenization

Bavesh Balaji, Pranav Gopinath, Pouya Sadeghi +1

Visual information worth extracting from an image and the token budget it warrants depend on the text query. Yet modern vision and vision-language models largely encode images inde…

cs.CV2026

MaskMerge: Structure-aware Token Merging for Efficient Instance Segmentation

Bavesh Balaji, Letian Jiang, Alexander Wong +2

Token merging improves the efficiency of Vision Transformers by combining redundant tokens, but existing methods largely rely on feature similarity to determine which tokens to mer…

cs.CV2026

Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation

Utku Cicek, Mahip Singh, Ziyao Shang +5

While foundation models and vision transformers (ViTs) have redefined visual representations, current active learning (AL) strategies for these backbones largely operate at the pat…

cs.CV2026

How Far Can INRs Go? Cross-Domain Parameter-efficient INR-Based Semantic Segmentation for Brain MRI

Ziyao Shang, Pouya Sadeghi, Letian Jiang +2

Biomedical image segmentation is central to medical image analysis, but practical deployment often faces limited annotations, memory constraints, and cross-site distribution shifts…

cs.CV2026

PinPoint: Prompting with Informative Interior Points

Pouya Sadeghi, Shawn He, Pedro Pablo Guerrero Vela +3

Modern referring image segmentation pipelines couple a vision-language model (VLM) for grounding with a promptable segmenter such as the Segment Anything Model (SAM) for mask gener…

cs.CV2026

Zero-Shot Object Re-Identification in Egocentric Kitchen Videos via Multi-Stage SAM3 Feature Fusion

Dmytro Klepachevskyi, Alexander Wong, Sirisha Rambhatla +1

Object re-identification (ReID) in egocentric kitchen videos is challenging due to rapid viewpoint changes, frequent occlusions, cluttered scenes, and large intra-class appearance…

cs.CV2025

Avatar4D: Synthesizing Domain-Specific 4D Humans for Real-World Pose Estimation

Jerrin Bright, Zhibo Wang, Dmytro Klepachevskyi +4

We present Avatar4D, a real-world transferable pipeline for generating customizable synthetic human motion datasets tailored to domain-specific applications. Unlike prior works, wh…

cs.CV2025

LOCATEdit: Graph Laplacian Optimized Cross Attention for Localized Text-Guided Image Editing

Achint Soni, Meet Soni, Sirisha Rambhatla

Text-guided image editing aims to modify specific regions of an image according to natural language instructions while maintaining the general structure and the background fidelity…

cs.CV2025

LangDA: Building Context-Awareness via Language for Domain Adaptive Semantic Segmentation

Chang Liu, Bavesh Balaji, Saad Hossain +5

Unsupervised domain adaptation for semantic segmentation (DASS) aims to transfer knowledge from a label-rich source domain to a target domain with no labels. Two key approaches in…

cs.CV2024

Domain-Guided Masked Autoencoders for Unique Player Identification

Bavesh Balaji, Jerrin Bright, Sirisha Rambhatla +4

Unique player identification is a fundamental module in vision-driven sports analytics. Identifying players from broadcast videos can aid with various downstream tasks such as play…

cs.CV2023

Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?

Jinman Park, Francois Barnard, Saad Hossain +2

Unsupervised domain adaptation (UDA) aims to bridge the gap between source and target domains in the absence of target domain labels using two main techniques: input-level alignmen…

cs.CV2022

Building Spatio-temporal Transformers for Egocentric 3D Pose Estimation

Jinman Park, Kimathi Kaai, Saad Hossain +3

Egocentric 3D human pose estimation (HPE) from images is challenging due to severe self-occlusions and strong distortion introduced by the fish-eye view from the head mounted camer…

cs.CV2020★ 4 cited

Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes

Loc Trinh, Michael Tsang, Sirisha Rambhatla +1

In this paper we propose a novel human-centered approach for detecting forgery in face images, using dynamic prototypes as a form of visual explanations. Currently, most state-of-t…

cs.CV2019★ 13 cited

A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing

Sirisha Rambhatla, Xingguo Li, Jineng Ren +1

We consider the task of localizing targets of interest in a hyperspectral (HS) image based on their spectral signature(s), by posing the problem as two distinct convex demixing tas…