  In this paper, we study the $L^p(\mathbb{R}^2)$-improving bounds, i.e.,
$L^p(\mathbb{R}^2)\rightarrow L^q(\mathbb{R}^2)$ estimates, of the maximal
function $M_{\gamma}$ along a plane curve $(t,\gamma(t))$, where
  $$M_{\gamma}f(x_1,x_2):=\sup_{u\in [1,2]}\left|\int_{0}^{1}f(x_1-ut,x_2-u
\gamma(t))\,\textrm{d}t\right|,$$
  and $\gamma$ is a general plane curve satisfying some suitable smoothness and
curvature conditions. We obtain $M_{\gamma} : L^p(\mathbb{R}^2)\rightarrow
L^q(\mathbb{R}^2)$ if $(\frac{1}{p},\frac{1}{q})\in \Delta\cup \{(0,0)\}$ and
$(\frac{1}{p},\frac{1}{q})$ satisfying $1+(1
+\omega)(\frac{1}{q}-\frac{1}{p})>0$, where
$\Delta:=\{(\frac{1}{p},\frac{1}{q}):\ \frac{1}{2p}<\frac{1}{q}\leq
\frac{1}{p}, \frac{1}{q}>\frac{3}{p}-1 \}$ and $\omega:=\limsup_{t\rightarrow
0^{+}}\frac{\ln|\gamma(t)|}{\ln t}$. This result is sharp except for some
borderline cases. As Hickman stated in [J. Funct. Anal. 270 (2016), pp.
560--608], this is a very different situation.
