Yes. The reason is that the map $s\mapsto u_s$ is continuous in $L^2$ norm (even Hölder continuous, with exponent $1/2$).
Let $F(s)$ be the minimal value of the functional we're minimizing, and let $v_s$ be the restriction of $v$ to the moving domain. Note that $v_s$ and $v_t$ differ by at most $C|s-t|$ in the $L^2$ norm.
Consider two values $s,t$ with minimizers $u_s, u_t$. Let $u=(u_s+u_t)/2$.
By the parallelogram law, for any function $g\in L^2$ we have
$$
\|u-g\|_2^2 \le \frac{1}{2}(\|u_s-g\|_2^2 + \|u_t-g\|_2^2) - \frac{1}{4}\|u_s-u_t\|_2^2
\tag{1}$$
(The parallelogram has vertices $g$, $u_s$, $u_t$, and center point $u$.) Additionally,
$$|u|_{TV}\le \frac12(|u_t|_{TV} + |u_s|_{TV})\tag2$$ by the triangle inequality.
The inequalities (1) and (2) imply that if $u_t-u_s$ has large $L^2$ norm, the average $u$ becomes preferable to either of them for the purpose of minimization, contradicting the minimizing properties of $u_t, u_s$.
To verify this, use (1) with $g=v_s$, then with $g=v_t$, and add the results:
$$
(\|u-v_s\|_2^2 + |u|_{TV}) +
(\|u-v_t\|_2^2 + |u|_{TV})
\le
\frac12(\|u_t-v_s\|_2^2 + \|u_t-v_t\|_2^2) + |u_t|_{TV}
+ \frac12(\|u_s-v_s\|_2^2 + \|u_s-v_t\|_2^2 ) + |u_s|_{TV} - \frac{1}{4}\|u_s-u_t\|^2
$$
Since $v_t$ and $v_s$ are close, the right hand side is at most $$F(t)+F(s)+ C\|v_t-v_s\|_2 - \frac{1}{4}\|u_s-u_t\|_2^2 $$ But the left hand is at least $F(t)+F(s)$. Hence,
$\|u_s-u_t\|_2^2 \le C\|v_t-v_s\|_2$ as claimed.