1.0Slot4D: Learning Object Slots for 4D Reconstructionhttps://mscvprojects.ri.cmu.edu/2026teamf7Experiments - Slot4D: Learning Object Slots for 4D Reconstructionrich600338<blockquote class="wp-embedded-content" data-secret="z0eSDyHAH9"><a href="https://mscvprojects.ri.cmu.edu/2026teamf7/experiments/">Experiments</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2026teamf7/experiments/embed/#?secret=z0eSDyHAH9" width="600" height="338" title="“Experiments” — Slot4D: Learning Object Slots for 4D Reconstruction" data-secret="z0eSDyHAH9" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
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Baseline Removing the dropout from slot attention head improves performance Baseline fails at identifying smaller objects and have blur boundaries. Remove Dropout Removing the dropout from slot attention head improves performance Background/Foreground Aware Strategy Identifying the background first helps to separate objects from the background. Geometric Consistency Loss Encourages slots to align with consistent 3D […]https://mscvprojects.ri.cmu.edu/2026teamf7/wp-content/uploads/sites/149/2026/05/Screenshot-2026-05-05-at-10.28.30-PM-1.png1354572