most citedDynaPURLS: Dynamic Refinement of Part-Aware Representations for Skeleton-Based Zero-Shot Action Recognition

1 citations · 2 across the 13 of their papers we have counts for

collaborators

18 papers

cs.CV2026

VideoSlate: Stateful Commit Control for Temporally Grounded Agentic Video Reasoning

Shuo Zheng, Yuanjie Dang, Peng Chen +4

Agentic video reasoning systems gather and assess video evidence across stages, selecting relevant spans as visual evidence for answering questions. New candidates and observations…

cs.SD2026

SAVU-BENCH: A Real-World Benchmark for Spatial Audio-Visual Understanding

Yu Chen, Ruihang Liu, Yangguang Xu +5

Spatial audio-visual understanding requires models to recognize not only what is present, but also where events occur and how they relate across modalities. Existing benchmarks oft…

cs.CV2026

NeuralSRNF: Neural Square Root Normal Fields for the Statistical Shape Analysis and Generation of Nonrigid 3D and 4D Objects

Awais Nizamani, Hamid Laga, Guanjin Wang +3

We introduce NeuralSRNF, a novel framework for the statistical shape analysis and generation of genus-zero 3D and 4D objects that undergo nonrigid deformations. Traditional methods…

cs.CV2026

TreeSRNF: Square-Root Normal Fields for Generative Modelling of the Geometric and Structural Variability in Tree-like 3D Objects

Tahmina Khanam, Hamid Laga, Mohammed Bennamoun +4

We introduce a novel mathematical framework for analyzing and generating complex tree-shaped 3D objects, such as botanical trees and plants, which deform both in their 3D geometry…

cs.CV2026

Learning Structured Visual Compositional Representations for Weakly Supervised Referring Expression Comprehension

Lian Xu, Mohammed Bennamoun, Farid Boussaid +3

Referring expression comprehension (REC) aims to localize the object in an image described by natural language. In Weakly supervised REC (WREC), existing approaches primarily opera…

cs.CV2026

SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition

Yanan Liu, Anqi Zhu, Jingmin Zhu +6

Skeleton-based action recognition aims to understand human behaviors from body joint sequences and is especially challenging in the one-shot setting, where only a single labeled ex…

cs.CL2026

When Rewards Disagree: Reward Weighting for Token-Efficient Video Reasoning

Zinuo Li, Yongxin Guo, Jun Liu +7

Human perception interprets video dynamics by constructing structured mental representations of entities, actions, and temporal boundaries before engaging in high-level reasoning.…

cs.CV2026

SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition

Ning Wang, Tieyue Wu, Naeha Sharif +5

Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typ…

cs.CV2026

Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades

Ashkan Taghipour, Morteza Ghahremani, Zinuo Li +3

Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally…

cs.CV2026

Fact or Fake? Assessing the Role of Deepfake Detectors in Multimodal Misinformation Detection

A S M Sharifuzzaman Sagar, Mohammed Bennamoun, Farid Boussaid +4

In multimodal misinformation, deception usually arises not just from pixel-level manipulations in an image, but from the semantic and contextual claim jointly expressed by the imag…

cs.CV2025★ 1 cited

DynaPURLS: Dynamic Refinement of Part-Aware Representations for Skeleton-Based Zero-Shot Action Recognition

Jingmin Zhu, Anqi Zhu, James Bailey +5

Zero-shot skeleton-based action recognition (ZS-SAR) is fundamentally constrained by prevailing approaches that rely on aligning skeleton features with static, class-level semantic…

cs.CV2025

Hybrid Transformer-Mamba for Weakly Supervised Volumetric Medical Segmentation

Yiheng Lyu, Lian Xu, Coen Arrow +3

Weakly supervised segmentation enables model training from plane-level labels. Existing methods often rely on 2D encoders, neglecting the volumetric nature of medical data. We prop…

cs.CV2025

AdaRD-key: Adaptive Relevance-Diversity Keyframe Sampling for Long-form Video understanding

Xian Zhang, Zexi Wu, Zinuo Li +5

Understanding long-form videos remains a significant challenge for vision--language models (VLMs) due to their extensive temporal length and high information density. Most current…

cs.CV2025

SVR-GS: Spatially Variant Regularization for Probabilistic Masks in 3D Gaussian Splatting

Ashkan Taghipour, Vahid Naghshin, Benjamin Southwell +3

3D Gaussian Splatting (3DGS) enables fast, high-quality novel view synthesis but typically relies on densification followed by pruning to optimize the number of Gaussians. Existing…

cs.CG2025

A Riemannian Framework for the Elastic Analysis of the Spatiotemporal Variability in the Shape and Structure of Tree-like 4D Objects

Tahmina Khanam, Hamid Laga, Mohammed Bennamoun +5

This paper introduces a novel computational framework for modeling and analyzing the spatiotemporal shape variability of tree-like 4D structures whose shapes deform and evolve over…

cs.CV2025

LatentMove: Towards Complex Human Movement Video Generation

Ashkan Taghipour, Morteza Ghahremani, Mohammed Bennamoun +5

Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often s…

cs.CL2025

Watch and Listen: Understanding Audio-Visual-Speech Moments with Multimodal LLM

Zinuo Li, Xian Zhang, Yongxin Guo +5

Humans naturally understand moments in a video by integrating visual and auditory cues. For example, localizing a scene in the video like "A scientist passionately speaks on wildli…

cs.CV2025★ 1 cited

GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing

Akashah Shabbir, Mohammed Zumri, Mohammed Bennamoun +2

Recent advances in large multimodal models (LMMs) have recognized fine-grained grounding as an imperative factor of visual understanding and dialogue. However, the benefits of such…