arXiv (All)
open access
LoopTrack: A Simple Baseline for Parameter-Efficient Transformer Tracking
Current Transformer-based tracking methods typically stack multiple Transformer blocks with separate parameters to model interactions between the target template and the search region for target localization. These trackers often incur substantial parameter overhead from stacked blocks, making their
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- FINN-ViT: End-to-End Compilation of Vision Transformers to Streaming Dataflow FPGAs#1175265
- LoopSpec: Pipelined Self-Speculative Decoding for Looped Transformers#1123569
- LoopSpec: Pipelined Self-Speculative Decoding for Looped Transformers#919396
- LoopVL: Recurrent Visual Intelligence#1143027
- TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking#182757
Record · ID 1118018
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive