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20232026
most citedQ-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models

2 citations · 4 across the 7 of their papers we have counts for

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cs.CV2026

Characterizing Detectability in 3DGS Poisoning: A Stage-wise Benchmark

Quoc-Anh Bui-Huynh, Thanh Duc Ngo, Xue Geng +4

3D Gaussian Splatting (3DGS) has rapidly emerged as a leading representation for real-time novel view synthesis, but recent work shows it is vulnerable to diverse poisoning attacks…

cs.CV2026

Joint Architecture-Token-Bitwidth Multi-Axis Optimization of Vision Transformers for Semiconductor IC Packaging

Phat Nguyen, Xue Geng, Kaixin Xu +3

Vision Transformers (ViTs) have achieved strong performance in visual recognition, yet their deployment in resource-constrained industrial environments remains limited. The main ch…

cs.CV2024

DM3D: Distortion-Minimized Weight Pruning for Lossless 3D Object Detection

Kaixin Xu, Qingtian Feng, Hao Chen +6

Applying deep neural networks to 3D point cloud processing has attracted increasing attention due to its advanced performance in many areas, such as AR/VR, autonomous driving, and…

cs.CV2024★ 1 cited

LPViT: Low-Power Semi-structured Pruning for Vision Transformers

Kaixin Xu, Zhe Wang, Chunyun Chen +7

Vision transformers have emerged as a promising alternative to convolutional neural networks for various image analysis tasks, offering comparable or superior performance. However,…

cs.CV2023★ 2 cited

Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models

Haoning Wu, Zicheng Zhang, Erli Zhang +11

Multi-modality foundation models, as represented by GPT-4V, have brought a new paradigm for low-level visual perception and understanding tasks, that can respond to a broad range o…