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From the 1 of 11 linked papers with an AI index.

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20242026
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11 papers

cs.CV2026

CLEAR: Conflict-aware Learning via Evidence-guided Adaptive Routing for Unified Sparse-View 3D Gaussian Super-Resolution

Hantang Li, Qiang Zhu, Xiandong Meng +2

Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and high-frequency information fo…

cs.CV2026

LAST: The Last Query Token Guides Visual Token Pruning for Edge-Cloud Collaborative MLLM Inference

Feng Yang, Xinrui Ju, Keyang Zhang +6

The paper introduces LAST, a training‑free method that uses the attention of the last query token to prune visual tokens on edge devices before sending them to a cloud multimodal L…

cs.CV2026

LUMI: Tokenizer-Agnostic LLM-Based Lossless Image Compression

Chris Xing Tian, Chengkai Wu, Ziyu Wang +6

Large language model (LLM)-based lossless image compression methods typically represent pixel data through the native text interface of a pretrained model, converting pixel values…

cs.CV2026

Neural Video Compression with Domain Transfer

Tiange Zhang, Rongqun Lin, Xiandong Meng +4

Content-adaptive compression has always been a key direction in neural video coding (NVC), aiming to mitigate the domain gap between training and testing data. Such gaps often aris…

cs.CV2026

PairDropGS: Paired Dropout-Induced Consistency Regularization for Sparse-View Gaussian Splatting

Hantang Li, Qiang Zhu, Xiandong Meng +3

Dropout-based sparse-view 3D Gaussian Splatting (3DGS) methods alleviate overfitting by randomly suppressing Gaussian primitives during training. Existing methods mainly focus on d…

cs.CV2026

NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results

Shuhong Liu, Chenyu Bao, Ziteng Cui +103

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to…