This paper presents a fault-tolerance technique for H.264's Context-Adaptive Variable Length Coding (CAVLC) on unreliable computing hardware. The application-specific knowledge is leveraged at both algorithm and architecture levels to protect the CAVLC process (especially context adaptation and coding tables) in a reliable yet power-efficient manner. Specifically, the statistical analysis of coding syntax and video content properties are exploited for: (1) selective redundancy of coefficient/header data of video bitstreams; (2) partitioning the coding tables into various sub-tables to reduce the power overhead of fault tolerance; and (3) run-time power management of memory parts storing the sub-tables and their parity computations. Experimental results demonstrate that leveraging application-specific knowledge reduces area and performance overhead by 2x compared to a double-parity table protection technique. For functional verification and area comparison, the complete H.264 CAVLC architecture is prototyped on a Xilinx Virtex-5 FPGA (though not limited to it).