AI RESEARCH
Characterizing Detectability in 3DGS Poisoning: A Stage-wise Benchmark
arXiv CS.CV
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ArXi:2606.03499v1 Announce Type: new 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, including illusory object injection, computation cost amplification, and post hoc model watermarking. Despite this expanding threat surface, existing studies focus mainly on attack success, while defense and detection remain underexplored.