\begin{figure}[!htbp]
    \centering
  \includegraphics[width=\linewidth]{figures/sam3_better.pdf}
 \caption{\textbf{Qualitative examples where SAM 3 outperforms SAM 2}. All examples show SAM~3's superior prompt initialization by better localizing the target even under sparse prompts, whereas SAM~2 fails to localize the target on the prompted frame and across the volume/sequence, resulting in flooding/over-segmentation and notably lower DSC. Moreover, in examples~1--2, the red-boxed columns (Example~1: slice $\ge$ 68; Example~2: slice $\ge$ 51) correspond to slices where the GT mask is empty (target absent); SAM~2 continues to produce residual masks beyond the last object frame, while SAM~3 terminates more cleanly. [Colors: \sethlcolor{gtMask}\hl{\texttt{GT}}, \sethlcolor{samTwoBase}\hl{\texttt{SAM 2}}, \sethlcolor{samThreeBase}\hl{\texttt{SAM 3}}]}
    \label{fig:sam3better}
\end{figure}
