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20212026
most citedVideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

11 citations · 31 across the 26 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays

Yang Zhou, Tan Li Hui Faith, Yanyu Xu +4

Medical Vision-Language Pretraining (MedVLP) shows promise in learning generalizable and transferable visual representations from paired and unpaired medical images and reports. Me…

cs.CV2024

Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss

Zesen Cheng, Hang Zhang, Kehan Li +6

Contrastive loss is a powerful approach for representation learning, where larger batch sizes enhance performance by providing more negative samples to better distinguish between s…

cs.CV2024

The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio

Sicong Leng, Yun Xing, Zesen Cheng +7

Recent advancements in large multimodal models (LMMs) have significantly enhanced performance across diverse tasks, with ongoing efforts to further integrate additional modalities…

cs.CV2024★ 2 cited

Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention

Wenbin An, Feng Tian, Sicong Leng +6

Despite great success across various multimodal tasks, Large Vision-Language Models (LVLMs) often encounter object hallucinations with generated textual responses being inconsisten…

cs.CV2024★ 11 cited

VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Zesen Cheng, Sicong Leng, Hang Zhang +8

In this paper, we present the VideoLLaMA 2, a set of Video Large Language Models (Video-LLMs) designed to enhance spatial-temporal modeling and audio understanding in video and aud…

cs.CV2024

Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly

Hang Du, Sicheng Zhang, Binzhu Xie +16

Video anomaly understanding (VAU) aims to automatically comprehend unusual occurrences in videos, thereby enabling various applications such as traffic surveillance and industrial…

cs.CV2024★ 1 cited

Constrained Layout Generation with Factor Graphs

Mohammed Haroon Dupty, Yanfei Dong, Sicong Leng +4

This paper addresses the challenge of object-centric layout generation under spatial constraints, seen in multiple domains including floorplan design process. The design process ty…