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20242026
most citedAIM 2024 Challenge on Video Saliency Prediction: Methods and Results

8 citations · 8 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

JavisGPT: A Unified Multi-modal LLM for Sounding-Video Comprehension and Generation

Kai Liu, Jungang Li, Yuchong Sun +13

This paper presents JavisGPT, the first unified multimodal large language model (MLLM) for joint audio-video (JAV) comprehension and generation. JavisGPT has a concise encoder-LLM-…

cs.CV2025

TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning

Tao Wu, Li Yang, Gen Zhan +6

Enhancing the temporal understanding of Multimodal Large Language Models (MLLMs) is essential for advancing long-form video analysis, enabling tasks such as temporal localization,…

cs.CV2025

From Sight to Insight: Unleashing Eye-Tracking in Weakly Supervised Video Salient Object Detection

Qi Qin, Runmin Cong, Gen Zhan +2

The eye-tracking video saliency prediction (VSP) task and video salient object detection (VSOD) task both focus on the most attractive objects in video and show the result in the f…

cs.CV20248 cited

AIM 2024 Challenge on Video Saliency Prediction: Methods and Results

Andrey Moskalenko, Alexey Bryncev, Dmitry Vatolin +30

This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provid…

cs.CV2024

CaRDiff: Video Salient Object Ranking Chain of Thought Reasoning for Saliency Prediction with Diffusion

Yolo Yunlong Tang, Gen Zhan, Li Yang +2

Video saliency prediction aims to identify the regions in a video that attract human attention and gaze, driven by bottom-up features from the video and top-down processes like mem…