activity
20192026
most citedHorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions

185 citations · 347 across the 38 of their papers we have counts for

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39 papers · 1 filter

cs.CV2026★ 7 cited

HOI-aware Adaptive Network for Weakly-supervised Action Segmentation

Runzhong Zhang, Suchen Wang, Yueqi Duan +3

In this paper, we propose an HOI-aware adaptive network named AdaAct for weakly-supervised action segmentation. Most existing methods learn a fixed network to predict the action of…

cs.CV2025

Pseudo Depth Meets Gaussian: A Feed-forward RGB SLAM Baseline

Linqing Zhao, Xiuwei Xu, Yirui Wang +5

Incrementally recovering real-sized 3D geometry from a pose-free RGB stream is a challenging task in 3D reconstruction, requiring minimal assumptions on input data. Existing method…

cs.CV2024★ 1 cited

Q-VLM: Post-training Quantization for Large Vision-Language Models

Changyuan Wang, Ziwei Wang, Xiuwei Xu +3

In this paper, we propose a post-training quantization framework of large vision-language models (LVLMs) for efficient multi-modal inference. Conventional quantization methods sequ…

cs.CV2024

GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generation

Chubin Zhang, Hongliang Song, Yi Wei +3

In this work, we introduce the Geometry-Aware Large Reconstruction Model (GeoLRM), an approach which can predict high-quality assets with 512k Gaussians and 21 input images in only…

cs.CV2024★ 1 cited

FlowIE: Efficient Image Enhancement via Rectified Flow

Yixuan Zhu, Wenliang Zhao, Ao Li +3

Image enhancement holds extensive applications in real-world scenarios due to complex environments and limitations of imaging devices. Conventional methods are often constrained by…

cs.CV2024

Narrative Action Evaluation with Prompt-Guided Multimodal Interaction

Shiyi Zhang, Sule Bai, Guangyi Chen +4

In this paper, we investigate a new problem called narrative action evaluation (NAE). NAE aims to generate professional commentary that evaluates the execution of an action. Unlike…