BitC-3DGS: High-Capacity 3D Gaussian Splatting Watermarking via Bit Compression

• URL: http://arxiv.org/abs/2605.29583v1
• Date: Thu, 28 May 2026 08:28:04 GMT
• Title: BitC-3DGS: High-Capacity 3D Gaussian Splatting Watermarking via Bit Compression
• Abstract summary: High-capacity watermarking is necessary for 3D Gaussian Splatting (3DGS) assets to embed rich information.<n>Existing bit-to-token watermarking methods are limited to 77-bit messages due to CLIP's fixed 77-token context length.<n>We introduce BitC-3DGS, a bit-compression framework that encodes multiple message bits per token.
• Score: 68.33622936663876
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: High-capacity watermarking is necessary for 3D Gaussian Splatting (3DGS) assets to embed rich information (e.g., ownership, provenance, and authentication codes), enabling reliable identification and integrity verification in large-scale 3D asset pipelines. Existing bit-to-token watermarking methods based on a pre-trained text encoder are limited to 77-bit messages due to CLIP's fixed 77-token context length, as tokens beyond this limit are unsupported by learned positional embeddings. To address this limitation, we introduce BitC-3DGS, a bit-compression framework that encodes multiple message bits per token. It employs a bit-compressed tokenization scheme that encodes multiple bits within the same chunk into a single semantic token. To enable recovery of the compressed information, it further introduces a dual-branch architecture for joint chunk decompression and bit decoding, along with a hard-message sampling strategy to improve combinatorial coverage during decoder training. Extensive experiments on the Blender and LLFF datasets demonstrate the effectiveness of BitC-3DGS for high-capacity watermarking, achieving high message recovery accuracy and rendering fidelity. For example, it supports 128-bit message capacity with recovery accuracy comparable to that of 64-bit messages in recent state-of-the-art methods.

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