activity
20242026
collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2026

AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects

Danrui Li, Jiahao Zhang, Bernhard Egger +4

Assembling objects from parts requires understanding multimodal instructions, linking them to 3D components, and predicting physically plausible 6-DoF motions for each assembly ste…

cs.CV2026

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models

Furkan Mumcu, Michael J. Jones, Anoop Cherian +1

Recent video anomaly detection research has expanded rapidly with an emphasis on general models of normality intended to work across many different scenes. While this focus has led…

cs.CV2025

WISE: Weighted Iterative Society-of-Experts for Robust Multimodal Multi-Agent Debate

Anoop Cherian, River Doyle, Eyal Ben-Dov +2

Recent large language models (LLMs) are trained on diverse corpora and tasks, leading them to develop complementary strengths. Multi-agent debate (MAD) has emerged as a popular way…

cs.CV2025

Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection

Furkan Mumcu, Michael J. Jones, Anoop Cherian +1

Existing semi-supervised video anomaly detection (VAD) methods often struggle with detecting complex anomalies involving object interactions and generally lack explainability. To o…

cs.CV2025

MMHOI: Modeling Complex 3D Multi-Human Multi-Object Interactions

Kaen Kogashi, Anoop Cherian, Meng-Yu Jennifer Kuo

Real-world scenes often feature multiple humans interacting with multiple objects in ways that are causal, goal-oriented, or cooperative. Yet existing 3D human-object interaction (…

cs.CV2025

LLM-Guided Agentic Object Detection for Open-World Understanding

Furkan Mumcu, Michael J. Jones, Anoop Cherian +1

Object detection traditionally relies on fixed category sets, requiring costly re-training to handle novel objects. While Open-World and Open-Vocabulary Object Detection (OWOD and…