activity
20152026
most citedExtremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM

80 citations · 190 across the 12 of their papers we have counts for

collaborators

14 papers

cs.RO2026

GeoScaffold: Learning Compact Geometric Latents via Reconstruction for Efficient Vision-Language Navigation

Yixuan Jiang, Wentong Li, An Liu +5

Recent vision-and-language navigation (VLN) systems increasingly adopt streaming Video-LLM policies that map egocentric RGB observations and instructions directly to low-level acti…

cs.RO2026

HAM-VLN: Harnessing Hierarchical Agentic Memory for Zero-Shot Vision-and-Language Navigation

An Liu, Bingxi Liu, Hongyu Ding +6

Vision-and-language navigation (VLN) enables robots to follow instructions in previously unseen environments. Recently, a training-free paradigm has emerged: the robot queries a mu…

eess.IV2022★ 1 cited

Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report

Marcos V. Conde, Radu Timofte, Yibin Huang +40

Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous low-level…

cs.CV2022★ 3 cited

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

Furkan Kınlı, Sami Menteş, Barış Özcan +30

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…

eess.IV2022★ 16 cited

AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Xin Li +49

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…

cs.CV2021

Architecture Aware Latency Constrained Sparse Neural Networks

Tianli Zhao, Qinghao Hu, Xiangyu He +4

Acceleration of deep neural networks to meet a specific latency constraint is essential for their deployment on mobile devices. In this paper, we design an architecture aware laten…