activity
20232025
most citedFollow the Rules: Reasoning for Video Anomaly Detection with Large Language Models

3 citations · 3 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2025

Task-Aware Resolution Optimization for Visual Large Language Models

Weiqing Luo, Zhen Tan, Yifan Li +4

Real-world vision-language applications demand varying levels of perceptual granularity. However, most existing visual large language models (VLLMs), such as LLaVA, pre-assume a fi…

cs.CV2025

Contact-Aware Amodal Completion for Human-Object Interaction via Multi-Regional Inpainting

Seunggeun Chi, Enna Sachdeva, Pin-Hao Huang +1

Amodal completion, which is the process of inferring the full appearance of objects despite partial occlusions, is crucial for understanding complex human-object interactions (HOI)…

cs.CV2025

Occlusion-Aware Temporally Consistent Amodal Completion for 3D Human-Object Interaction Reconstruction

Hyungjun Doh, Dong In Lee, Seunggeun Chi +4

We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsist…

cs.LG2025

Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer

Huaizhi Qu, Inyoung Choi, Zhen Tan +6

LLM ensembles are widely used for LLM judges. However, how to estimate their accuracy, especially in an efficient way, is unknown. In this paper, we present a principled maximum a…

cs.CL2025

GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks

Haoqiang Kang, Enna Sachdeva, Piyush Gupta +2

Vision-Language Models (VLMs) have recently shown promising advancements in sequential decision-making tasks through task-specific fine-tuning. However, common fine-tuning methods,…

cs.CV2025

Can Hallucination Correction Improve Video-Language Alignment?

Lingjun Zhao, Mingyang Xie, Paola Cascante-Bonilla +2

Large Vision-Language Models often generate hallucinated content that is not grounded in its visual inputs. While prior work focuses on mitigating hallucinations, we instead explor…

cs.RO2025

Generalized Mission Planning for Heterogeneous Multi-Robot Teams via LLM-constructed Hierarchical Trees

Piyush Gupta, David Isele, Enna Sachdeva +4

We present a novel mission-planning strategy for heterogeneous multi-robot teams, taking into account the specific constraints and capabilities of each robot. Our approach employs…

cs.CV2024

Estimating Ego-Body Pose from Doubly Sparse Egocentric Video Data

Seunggeun Chi, Pin-Hao Huang, Enna Sachdeva +3

We study the problem of estimating the body movements of a camera wearer from egocentric videos. Current methods for ego-body pose estimation rely on temporally dense sensor data,…

cs.AI2024

Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge

Weihua Du, Qiushi Lyu, Jiaming Shan +8

We introduce Constrained Human-AI Cooperation (CHAIC), an inclusive embodied social intelligence challenge designed to test social perception and cooperation in embodied agents. In…

cs.CV2024★ 3 cited

Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models

Yuchen Yang, Kwonjoon Lee, Behzad Dariush +2

Video Anomaly Detection (VAD) is crucial for applications such as security surveillance and autonomous driving. However, existing VAD methods provide little rationale behind detect…

cs.CV2023

ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models

Kaiwen Zhou, Kwonjoon Lee, Teruhisa Misu +1

In our work, we explore the synergistic capabilities of pre-trained vision-and-language models (VLMs) and large language models (LLMs) on visual commonsense reasoning (VCR) problem…