added link to concurrent works, hybridgs and t-3dgs

AaltoML · Dec 8, 2024 · 87bb6ac · 87bb6ac
1 parent 0723db9
commit 87bb6ac
Showing 1 changed file with 13 additions and 5 deletions.
diff --git a/index.html b/index.html
@@ -332,11 +332,19 @@ <h2 class="title is-3">Related Links</h2>
           <p>
             Check out some interesting works related to distractor-free Gaussian splatting: 
             <ul>
-              <li> <a href="https://spotlesssplats.github.io/">SpotLessSplats: Ignoring Distractors in 3D Gaussian Splatting. </li>
-              <li> <a href="https://github.com/jkulhanek/wild-gaussians/">WildGaussians: 3D Gaussian Splatting in the Wild. </li>
-              <li> <a href="https://arxiv.org/abs/2403.10427">SWAG: Splatting in the Wild images with Appearance-conditioned Gaussians. </li>
-              <li> <a href="https://eastbeanzhang.github.io/GS-W/">Gaussian in the Wild: 3D Gaussian Splatting for Unconstrained Image Collections. </li>
-              <li> <a href="https://arxiv.org/abs/2406.10373">Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections </li>   
+              <li> <a href="https://spotlesssplats.github.io/">SpotLessSplats: Ignoring Distractors in 3D Gaussian Splatting.</a> </li>
+              <li> <a href="https://github.com/jkulhanek/wild-gaussians/">WildGaussians: 3D Gaussian Splatting in the Wild.</a> </li>
+              <li> <a href="https://arxiv.org/abs/2403.10427">SWAG: Splatting in the Wild images with Appearance-conditioned Gaussians.</a> </li>
+              <li> <a href="https://eastbeanzhang.github.io/GS-W/">Gaussian in the Wild: 3D Gaussian Splatting for Unconstrained Image Collections.</a> </li>
+              <li> <a href="https://arxiv.org/abs/2406.10373">Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections.</a> </li>   
+            </ul>
+          </p>
+          <p>
+            There are also some exciting, ßconcurrent works that was introduced around the same time as ours:
+            <ul>
+              <li> <a href="https://gujiaqivadin.github.io/hybridgs/">HybridGS</a> introduces an idea similar to our explicit separation of distractors and static elements by modeling these with 2DGS and 3DGS respectively. </li>
+              <li> <a href="https://transient-3dgs.github.io/">T-3DGS</a> focus on removing distractors from input videos for reconstruction with 3DGS and employs Segment Anything Model (SAM) for refining transient masks. 
+              </li> 
             </ul>
           </p>
         </div>